Metadata Governance is the execution and enforcement of authority over the management of Metadata and other data documentation. Organizations that govern their data documentation find it easier to govern their data as a result. There is direct correlation between the use of Data Catalogs, Business Glossaries and Data Dictionaries and successful governance of data and Metadata.
This monthās RWDG webinar with Bob Seiner will focus on governing the use of the mentioned tools and the Metadata that can be managed inside each one. Bob will talk about governing Metadata in existing Metadata resources versus using new tools to handle this function.
In this webinar, Bob will discuss:
- The relationship between Data Governance and Metadata Governance
- Metadata collected in Data Catalogs, Business Glossaries, and Data Dictionaries
- How to maximize use the data documentation in each resource
- Governing data documentation in Catalogs, Glossaries, and Dictionaries
- Measuring the effectiveness of governed Metadata
RWDG Slides: Data Governance Roles and ResponsibilitiesDATAVERSITY
Ā
Roles and responsibilities are the backbone to a successful Data Governance program. The way you define and utilize the roles will be the biggest factor of program success. From data stewards to the steering committee and everyone in between, people will need to understand the role they play, why they are in the role, and how the role fits in with their existing job.
Join Bob Seiner for this RWDG webinar, where he will provide a complete and detailed set of Data Governance roles and responsibilities. Bob will share an operating model of roles and responsibilities that can be customized to address the specific needs of your organization.
In this webinar, Bob will discuss:
ā¢ Executive, strategic, tactical, operational, and support-level roles
ā¢ How to customize an operating model to fit your organization
ā¢ Detailed responsibilities for each level
ā¢ Defining who participates at each level
ā¢ Using working teams to implement tactical solutions
RWDG Slides: What is a Data Steward to do?DATAVERSITY
Ā
Most people recognize that Data Stewards play an essential role in their Data Governance and Information Governance programs. However, the manner in which Data Stewards are used is not the same from organization to organization. How you use Data Stewards depends on your goals for Data Governance.
Join Bob Seiner for this monthās RWDG webinar where he will share different ways to activate Data Stewards based on the purpose of your program. Bob will talk about options to extend existing Data Steward activity and how to build new functionality into the role of your Data Stewards.
In this webinar, Bob will discuss:
- The crucial role of the Data Steward in Data Governance
- Different types of Data Stewards and what they do
- Aligning Data Steward activities with program goals
- Improving existing Data Steward actions
- Finding new ways to use your Data Stewards
RWDG Slides: Applying Governance to Business ProcessesDATAVERSITY
Ā
This document discusses applying governance to business processes. It begins by defining key terms like data governance, data stewardship, and non-invasive data governance. It then discusses how data governance is not a single process, but the application of governance to various business processes using the components of the data governance framework, including roles, processes, communications, metrics, and tools. The document provides examples of processes that can be governed and emphasizes that the goal is to involve the right roles in processes to achieve the right results.
RWDG Slides: Achieving Data Quality with Data GovernanceDATAVERSITY
Ā
To improve Data Quality, organizations must focus on improving three data-related activities ā the definition, production, and usage of the data. Formalizing accountability for these activities strengthens the stewardsā ability to influence improvements in the quality of the data.
In this RWDG webinar, Bob Seiner and his guest, Anthony J. Algmin, will share examples of how organizations have focused their Data Governance programs on achieving improvements in Data Quality. The delivery of the program must advocate and enhance the delivery of standards, validation, reporting, and data value improvement. You may be surprised by how that delivery can be simplified.
In this webinar, Bob will talk about:
ā¢ The relationship between Data Governance and Data Quality
ā¢ The activities of defining, producing, and using data
ā¢ Stewards influencing improvements in Data Quality
ā¢ Standardization and validation of data through Data Governance
ā¢ Simplifying Data Governanceās purpose toward Data Quality
RWDG Slides: Data and Metadata Will Not Govern ThemselvesDATAVERSITY
Ā
There is a direct relationship between the value your organization gets from its data, the trust your organization has in its data, and how formally that data is being governed. This is not new news. In fact, this has always been the case.
Join Bob Seiner for the RWDG webinar to kick off the year, where he will discuss how data does not naturally or automatically increase in value or become more trusted without a resolute effort. That effort focuses on governance. The webinar will focus on the effort that must be orchestrated at the strategic, tactical, and operational levels of the organization to demonstrate value and gain the trust of the people at all levels.
In this webinar, Bob will share:
ā¢ How governance applies equally to data and metadata
ā¢ The meaning of a āresolute effortā to govern important assets
ā¢ How the governance of data and metadata increases their value
ā¢ The people who must be held formally accountable for data and metadata
ā¢ Communicating the webinarās title with people who can make a difference
Data Governance vs. Information GovernanceDATAVERSITY
Ā
What is the difference between Data Governance and information governance? Organizations either use these terms interchangeably ā or they have a distinct, separate meaning. Either way, it is important to discuss the discipline of governance as it pertains to different types of data and information ā and what the discipline is called.
Join Bob Seiner for this important RWDG webinar where he will share examples of organizations using each term, what it has meant for them, where their focuses have been, and how the terminology is evolving over time. A lot has been written about Data Governance and information governance. However, it is time to compare and contrast these disciplines and make a decision as to the right name to call it in your organization.
This webinar will focus on:
ā¢ Similarities and differences between data and information
ā¢ Definitions of data and information governance
ā¢ Examples of how organizations have selected their label
ā¢ Brief case studies of governance named both ways
ā¢ Considerations for naming your program
RWDG Slides: Glossaries, Dictionaries, and Catalogs Result in Data GovernanceDATAVERSITY
Ā
If you have the discipline to develop, deliver, and maintain a business glossary, data dictionary, and/or a data catalog, you may already have the makings of a Data Governance program. The roles required to deliver these assets can translate to successful Data Governance in several ways.
In this monthās webinar, Bob Seiner will highlight the aspects of delivering these valuable business assets that result in formal Data Governance. It is practical that your program recognize existing efforts to formalize the definition, production, and usage of data.
Topics to be discussed in this webinar:
ā¢ How glossaries, dictionaries, and catalogs add value
ā¢ What should be included in these assets
ā¢ Who has responsibility for these assets
ā¢ When these assets will be valuable to your organization
ā¢ Where the discipline results in Data Governance
A metadata framework delivers an improved understanding of metadata and how it is structured to improve the value of data. The development of a metadata framework must be easy to replicate for all of the critical data elements of the organization. The framework must also relate to the use of business glossaries, data dictionaries, and data catalogs.
In this RWDG webinar, Bob Seiner will share a framework that can be applied in every organization. The framework he will share can be created for yourself and is reusable for all of the critical data elements in your organization. You will walk away from this webinar thinking about how to apply the framework to your organizationās most important metadata.
RWDG Slides: Data Governance Roles and ResponsibilitiesDATAVERSITY
Ā
Roles and responsibilities are the backbone to a successful Data Governance program. The way you define and utilize the roles will be the biggest factor of program success. From data stewards to the steering committee and everyone in between, people will need to understand the role they play, why they are in the role, and how the role fits in with their existing job.
Join Bob Seiner for this RWDG webinar, where he will provide a complete and detailed set of Data Governance roles and responsibilities. Bob will share an operating model of roles and responsibilities that can be customized to address the specific needs of your organization.
In this webinar, Bob will discuss:
ā¢ Executive, strategic, tactical, operational, and support-level roles
ā¢ How to customize an operating model to fit your organization
ā¢ Detailed responsibilities for each level
ā¢ Defining who participates at each level
ā¢ Using working teams to implement tactical solutions
RWDG Slides: What is a Data Steward to do?DATAVERSITY
Ā
Most people recognize that Data Stewards play an essential role in their Data Governance and Information Governance programs. However, the manner in which Data Stewards are used is not the same from organization to organization. How you use Data Stewards depends on your goals for Data Governance.
Join Bob Seiner for this monthās RWDG webinar where he will share different ways to activate Data Stewards based on the purpose of your program. Bob will talk about options to extend existing Data Steward activity and how to build new functionality into the role of your Data Stewards.
In this webinar, Bob will discuss:
- The crucial role of the Data Steward in Data Governance
- Different types of Data Stewards and what they do
- Aligning Data Steward activities with program goals
- Improving existing Data Steward actions
- Finding new ways to use your Data Stewards
RWDG Slides: Applying Governance to Business ProcessesDATAVERSITY
Ā
This document discusses applying governance to business processes. It begins by defining key terms like data governance, data stewardship, and non-invasive data governance. It then discusses how data governance is not a single process, but the application of governance to various business processes using the components of the data governance framework, including roles, processes, communications, metrics, and tools. The document provides examples of processes that can be governed and emphasizes that the goal is to involve the right roles in processes to achieve the right results.
RWDG Slides: Achieving Data Quality with Data GovernanceDATAVERSITY
Ā
To improve Data Quality, organizations must focus on improving three data-related activities ā the definition, production, and usage of the data. Formalizing accountability for these activities strengthens the stewardsā ability to influence improvements in the quality of the data.
In this RWDG webinar, Bob Seiner and his guest, Anthony J. Algmin, will share examples of how organizations have focused their Data Governance programs on achieving improvements in Data Quality. The delivery of the program must advocate and enhance the delivery of standards, validation, reporting, and data value improvement. You may be surprised by how that delivery can be simplified.
In this webinar, Bob will talk about:
ā¢ The relationship between Data Governance and Data Quality
ā¢ The activities of defining, producing, and using data
ā¢ Stewards influencing improvements in Data Quality
ā¢ Standardization and validation of data through Data Governance
ā¢ Simplifying Data Governanceās purpose toward Data Quality
RWDG Slides: Data and Metadata Will Not Govern ThemselvesDATAVERSITY
Ā
There is a direct relationship between the value your organization gets from its data, the trust your organization has in its data, and how formally that data is being governed. This is not new news. In fact, this has always been the case.
Join Bob Seiner for the RWDG webinar to kick off the year, where he will discuss how data does not naturally or automatically increase in value or become more trusted without a resolute effort. That effort focuses on governance. The webinar will focus on the effort that must be orchestrated at the strategic, tactical, and operational levels of the organization to demonstrate value and gain the trust of the people at all levels.
In this webinar, Bob will share:
ā¢ How governance applies equally to data and metadata
ā¢ The meaning of a āresolute effortā to govern important assets
ā¢ How the governance of data and metadata increases their value
ā¢ The people who must be held formally accountable for data and metadata
ā¢ Communicating the webinarās title with people who can make a difference
Data Governance vs. Information GovernanceDATAVERSITY
Ā
What is the difference between Data Governance and information governance? Organizations either use these terms interchangeably ā or they have a distinct, separate meaning. Either way, it is important to discuss the discipline of governance as it pertains to different types of data and information ā and what the discipline is called.
Join Bob Seiner for this important RWDG webinar where he will share examples of organizations using each term, what it has meant for them, where their focuses have been, and how the terminology is evolving over time. A lot has been written about Data Governance and information governance. However, it is time to compare and contrast these disciplines and make a decision as to the right name to call it in your organization.
This webinar will focus on:
ā¢ Similarities and differences between data and information
ā¢ Definitions of data and information governance
ā¢ Examples of how organizations have selected their label
ā¢ Brief case studies of governance named both ways
ā¢ Considerations for naming your program
RWDG Slides: Glossaries, Dictionaries, and Catalogs Result in Data GovernanceDATAVERSITY
Ā
If you have the discipline to develop, deliver, and maintain a business glossary, data dictionary, and/or a data catalog, you may already have the makings of a Data Governance program. The roles required to deliver these assets can translate to successful Data Governance in several ways.
In this monthās webinar, Bob Seiner will highlight the aspects of delivering these valuable business assets that result in formal Data Governance. It is practical that your program recognize existing efforts to formalize the definition, production, and usage of data.
Topics to be discussed in this webinar:
ā¢ How glossaries, dictionaries, and catalogs add value
ā¢ What should be included in these assets
ā¢ Who has responsibility for these assets
ā¢ When these assets will be valuable to your organization
ā¢ Where the discipline results in Data Governance
A metadata framework delivers an improved understanding of metadata and how it is structured to improve the value of data. The development of a metadata framework must be easy to replicate for all of the critical data elements of the organization. The framework must also relate to the use of business glossaries, data dictionaries, and data catalogs.
In this RWDG webinar, Bob Seiner will share a framework that can be applied in every organization. The framework he will share can be created for yourself and is reusable for all of the critical data elements in your organization. You will walk away from this webinar thinking about how to apply the framework to your organizationās most important metadata.
Business Value Metrics for Data GovernanceDATAVERSITY
Ā
This document discusses how to quantify and communicate the business value of data governance initiatives. It begins with background on information capability and data maturity levels. It then discusses frameworks for understanding business value, such as key performance indicators and how initiatives can generate revenue, cost savings or avoidance. The document provides examples of how to calculate return on investment, net present value and payback period to quantify benefits. It also discusses how to effectively communicate a business case by aligning it with organizational objectives and knowing your audience.
RWDG Slides: Data Governance and Three Levels of Metadata ManagementDATAVERSITY
Ā
There are three levels of metadata that every organization must govern well. These levels are the semantic level, the business level, and the technical level. All three levels are important components of Data Governance and must be stewarded to focus on the goals and scope of your Data Governance program.
In this monthās installment of the Real-World Data Governance webinar series, Bob Seiner will present a three-tiered approach to defining, producing, and using all levels of metadata to further the cause of Data Governance. Governing the processes associated with this metadata tends to be a central focus of successful Data Governance programs. Join Bob to learn how to simplify the metadata focus.
In this webinar, Bob will discuss:
ā¢ The three levels of metadata and how they differ
ā¢ Sources of the metadata at each level
ā¢ Metadata linkage between the levels
ā¢ Processes to govern all the levels of metadata
ā¢ Institutionalizing policy to assure quality metadata at all levels
RWDG Webinar: Build Your Own Data Governance ToolsDATAVERSITY
Ā
<!-- wp:paragraph -->
<p>Data Governance tools can be enablers of program successā¦or the reason why Data Governance fails to meet peopleās expectations. Software tools can be leveraged or acquired from reliable vendors or developed internally to attempt to address your organizationās needs. Sometimes the best environment is made up of a combination of internal and external tools. What is a practitioner to do?</p>
<!-- /wp:paragraph -->
<!-- wp:paragraph -->
<p>Join Bob Seiner for this monthās RWDG webinar where he will share tools that you can build yourself and talk about how the tools can be used to determine requirements to acquire outside tools. Tools developed internally at little or no cost have helped to solve many Data Governance problems. Several of these problems and their solutions will be described in detail during this webinar.</p>
<!-- /wp:paragraph -->
<!-- wp:paragraph -->
<p>In this webinar, Bob will discuss:</p>
<!-- /wp:paragraph -->
<!-- wp:list -->
<ul><li>Several easy to build Data Governance tools</li><li>Customizing these tools to address specific issues</li><li>How internally developed tools can lead to tool acquisition</li><li>Knowing when it is time to acquire tools</li><li>Integrating DIY tools with acquired tools</li></ul>
<!-- /wp:list -->
RWDG Slides: Building Data Governance Through Data StewardshipDATAVERSITY
Ā
Data stewards play an important role in Data Governance solutions. That is why it is critical that organizations get data stewardship right when setting up their program. The data is governed by people. Some people will even tell you that the discipline should be called people governance.
Bob Seiner has a lot to say on this subject. In this RWDG webinar, Bob shares the reasons why you must build your Data Governance program through the stewardship of the data. There is no governance without formal accountability for data. People become stewards when their relationship to data is formalized. It is the only way.
This webinar will focus on:
ā¢ The definition of data stewardship that MUST be adopted
ā¢ The critical role stewardship plays in governing data
ā¢ What it means to formalize accountability
ā¢ Why everybody in the organization is a data steward
ā¢ How to build Data Governance through stewardship
Good data is like good water: best served fresh, and ideally well-filtered. Data Management strategies can produce tremendous procedural improvements and increased profit margins across the board, but only if the data being managed is of a high quality. Determining how Data Quality should be engineered provides a useful framework for utilizing Data Quality management effectively in support of business strategy, which in turns allows for speedy identification of business problems, delineation between structural and practice-oriented defects in Data Management, and proactive prevention of future issues.
Over the course of this webinar, we will:
Help you understand foundational Data Quality concepts based on āThe DAMA Guide to the Data Management Body of Knowledgeā (DAMA DMBOK), as well as guiding principles, best practices, and steps for improving Data Quality at your organization
Demonstrate how chronic business challenges for organizations are often rooted in poor Data Quality
Share case studies illustrating the hallmarks and benefits of Data Quality success
DataEd Slides: Approaching Data Governance StrategicallyDATAVERSITY
Ā
At its core, Data Governance (DG) is: managing data with guidance. This immediately provokes the question: Would you tolerate your data managed without guidance? (In all likelihood, your organization has been managing data without adequate guidance and this accounts for its current, less-than-optimal state.) This program provides a practical guide to implementing DG or recharging your existing program. It provides your organization with an understanding of what Data Governance functions are required and how they fit with other Data Management disciplines. Understanding these aspects is a necessary prerequisite to eliminate the ambiguity that often surrounds initial discussions and implement effective Data Governance/Stewardship programs that manage data in support of organizational strategy. Program learning objectives include:
ā¢ Understanding why Data Governance can be tricky for organizations due to dataās confounding characteristics
ā¢ Strategy No. 1: Keeping DG practically focused
ā¢ Strategy No. 2: DG must exist at the same level as HR
ā¢ Strategy No. 3: Gradually add ingredients
ā¢ Data Governance in action: storytelling
Trends in Enterprise Advanced AnalyticsDATAVERSITY
Ā
This document summarizes trends in enterprise analytics presented by William McKnight. It discusses the increasing importance of data and analytics for businesses. Key trends include greater use of data lakes, multi-cloud strategies, master data management, data virtualization, graph databases, stream processing, self-service analytics, and the rise of roles like Chief Data Officer. Data science and analytics skills will become more operational. Selection of big data platforms will consider factors like SQL support, data size, and workload complexity. Overall, data maturity correlates strongly with business success and organizations must continually advance to remain competitive.
In order to find value in your organizationās data assets, heroic Data Stewards are tasked with saving the dayāevery single day! These heroes adhere to a Data Governance framework and work to ensure that data is captured right the first time, validated through automated means, and integrated into business processes. Whether itās data profiling or in-depth root cause analysis, Data Stewards can be counted on to ensure the organizationās mission-critical data is reliable. In this webinar, we will approach this framework and punctuate important facets of a Data Stewardās role.
- Understand the business need for a Data Governance framework
- Learn why embedded Data Quality principles are an important part of system/process design
- Identify opportunities to help drive your organization to a data-driven culture
Data Governance and Metadata ManagementDATAVERSITY
Ā
Metadata is a tool that improves data understanding, builds end-user confidence, and improves the return on investment in every asset associated with becoming a data-centric organization. Metadataās use has expanded beyond ādata about dataā to cover every phase of data analytics, protection, and quality improvement. Data Governance and metadata are connected at the hip in every way possible. As the song goes, āYou canāt have one without the other.ā
In this RWDG webinar, Bob Seiner will provide a way to renew your energy by focusing on the valuable asset that can make or break your Data Governance programās success. The truth is metadata is already inherent in your data environment, and it can be leveraged by making it available to all levels of the organization. At issue is finding the most appropriate ways to leverage and share metadata to improve data value and protection.
Throughout this webinar, Bob will share information about:
- Delivering an improved definition of metadata
- Communicating the relationship between successful governance and metadata
- Getting your business community to embrace the need for metadata
- Determining the metadata that will provide the most bang for your bucks
- The importance of Metadata Management to becoming data-centric
Data Architecture - The Foundation for Enterprise Architecture and GovernanceDATAVERSITY
Ā
Organizations are faced with an increasingly complex data landscape, finding themselves unable to cope with exponentially increasing data volumes, compounded by additional regulatory requirements with increased fines for non-compliance. Enterprise architecture and data governance are often discussed at length, but often with different stakeholder audiences. This can result in complementary and sometimes conflicting initiatives rather than a focused, integrated approach. Data governance requires a solid data architecture foundation in order to support the pillars of enterprise architecture. In this session, IDERAās Ron Huizenga will discuss a practical, integrated approach to effectively understand, define and implement an cohesive enterprise architecture and data governance discipline with integrated modeling and metadata management.
Strategic imperative the enterprise data modelDATAVERSITY
Ā
With today's increasingly complex data ecosystems, the Enterprise Data Model (EDM) is a strategic imperative that every organization should adopt. An Enterprise Data Model provides context and consistency for all organizational data assets, as well as a classification framework for data governance. Enterprise modeling is also totally consistent with agile workflows, evolving incrementally to keep pace with changing organizational factors. In this session, IDERAās Ron Huizenga will discuss the increasing importance of the EDM, how it serves as a framework for all enterprise data assets, and provides a foundation for data governance.
The first step toward understanding what data assets mean for your organization is understanding what those assets mean for each other. Metadataāliterally, data about dataāis one of many Data Management disciplines inherent in good systems development and is perhaps the most mislabeled and misunderstood of the lot. Understanding metadata and its associated technologies as more than just straightforward technological tools can provide powerful insight into the efficiency of organizational practices and can also enable you to combine more sophisticated Data Management techniques in support of larger and more complex business initiatives.In this webinar, we will:Illustrate how to leverage Metadata Management in support of your business strategyDiscuss foundational metadata concepts based on the DAMA Guide to Data Management Book of Knowledge (DAMA DMBOK)Enumerate guiding principles for and lessons previously learned from metadata and its practical uses
RWDG Slides: A Complete Set of Data Governance Roles & ResponsibilitiesDATAVERSITY
Ā
The document discusses roles and responsibilities in data governance. It describes five levels of roles - executive, strategic, tactical, operational, and support. For each level, it provides examples of common roles and discusses customizing roles to an organization's structure. The webinar will cover defining roles at each level, who participates, and detailed responsibilities. It emphasizes starting with existing roles and terminology.
RWDG Slides: Build an Effective Data Governance FrameworkDATAVERSITY
Ā
Data Governance frameworks are used to structure the core components of a Data Governance program. Frameworks add significant value for those organizations getting started and improve or address missing components for programs already in place.
This monthās RWDG webinar with Bob Seiner will focus on dissecting a common Data Governance framework and customizing the framework to match the needs of your organization. Frameworks can be complex to describe but, in this case, the framework will become the self-describing face of your program.
In this webinar, Bob will share:
- A customizable Data Governance framework
- Five core components of a Data Governance framework
- Five perspectives for addressing each component
- Using a framework to select an approach to Data Governance
- Detailed descriptions of each component from each perspective
ADV Slides: What Happened of Note in 1H 2020 in Enterprise Advanced AnalyticsDATAVERSITY
Ā
Reassessing the information management marketplace for your enterprise direction on an annual basis is too infrequent. The technology is changing too fast. Data and analytic maturity levels rapidly evolve. What is advanced today may be entry-level in two years. Letās look at the high points for 1H 2020 in information management developments and how that may change what you are doing now. This can also be a strong data point for preparing 2021 budgets.
This document discusses governing master data. It defines key terms like data governance and data stewardship. It explains the connection between master data and data governance, and why master data needs to be governed. It discusses applying governance roles and responsibilities to master data processes. Finally, it concludes that master data governance is focusing a data governance program on improving an organization's master data.
RWDG Webinar: Agile Data Governance - How to Apply Governance to AgileDATAVERSITY
Ā
Agile development efforts and Data Governance efforts are at odds with each other. Even though they both have the sponsorship at the highest level of the organization, there is disconnect when it comes to understanding how the two disciplines interact. Supporters of both disciplines swear by their trade and leave little wiggle room when it comes to working together. Organizations want FAST and they require ACCURATE DATA. Organizations require both.
Bob Seiner will address Agile Data Governance in this monthās installment of the Real-World Data Governance webinar series. Agile efforts are typically corporate priority efforts. Data as an asset is an integral corporate priority. Both disciplines are here to stay to address rapidly changing business requirements and improved analytical and data protection capabilities. Organizations must address this separation and they must act quickly.
This webinar will focus on:
ā¢Relating the Disciplines for Senior Leadership
ā¢Finding Common Ground between Agile and Data Governance
ā¢Applying Data Governance to Agile Efforts
ā¢Best Practices for Agile Data Governance
ā¢Gaining Agile Support for Data Activities
Everybody is a Data Steward ā Get Over It!DATAVERSITY
Ā
When Data Stewardship is based on peopleās relationships to data, the program is assured to cover the entire organization. People that define, produce, and use data must be held formally accountable for their actions. That may include every person in your organization. Is this a good thing? Of course, it is.
Join Bob Seiner for this monthās installment of his Real-World Data Governance webinar series, where he will share how formalizing accountability, based on the actions people take with data, requires heightened awareness and enforcement of data rules. These rules focus on improving Data Quality, protecting sensitive data, and increasing peopleās knowledge of the data that adds value for their business.
In this webinar, Bob will discuss:
Why the āEverybody is a Data Stewardā approach is different (and better)
How to recognize the Data Stewards
Formalizing accountability based on data relationships
Coverage of the entire organization
Leveraging the technique to sell stewardship
Slides: Accelerate and Assure the Adoption of Cloud Data Platforms Using Inte...DATAVERSITY
Ā
Greater agility, scalability, and lower total cost of ownership made the decision to move key elements of your organizationās data capability to the cloud easy. The real challenge is migrating data from your legacy systems to your new cloud platform so you can unleash its potential and value while minimizing the migration risks.
Combining erwinās data modeling, governance, and intelligence solutions with Snowflakeās modern cloud data platform, organizations can realize a scalable, governed, and transparent enterprise data capability.
In this session, weāll show you how enterprise stakeholders with different skills and needs can work together to accelerate and assure the success of cloud migration projects of any size. Youāll learn how to:
ā¢ Reduce costs and mitigate risks when migrating legacy applications to Snowflake with erwinās model-driven schema design and transformation capabilities
ā¢ Increase the precision, speed, and agility of Snowflake deployments with erwin data automation
ā¢ Assure transparency, compliance, and governance for Snowflake data and processes
ā¢ Increase the efficiency and accuracy of analytics and other data usage on the Snowflake Cloud Platform
RWDG Webinar: DIY and Purchased Data Governance ToolsDATAVERSITY
Ā
Data Governance tools are enablers to program success. The metadata stored in these tools become the backbone of a successful Data Governance program. The question of whether to build your own Data Governance tools versus purchasing Data Governance tools must be answered early in the program development process. There are benefits and drawbacks to either way you answer this question.
This monthās RWDG webinar with Bob Seiner focuses on making smart choices when it comes to selecting or developing the tools to support your Data Governance program. Bob will share his experiences of evaluating tools on the market and also share templates and tools that he has created to assist programs through the growing pains of success. There is something in the webinar for newbies and experienced practitioners.
In this webinar Bob will address:
ā¢ How to answer the Build vs Buy question
ā¢ Criteria for evaluating tools on the market
ā¢ Examples of tools you can create yourself
ā¢ Complimentary nature of DIY and purchased tools
ā¢ Cost and benefits of Data Governance tool choices
RWDG Webinar: Using Data Governance to Improve Data UnderstandingDATAVERSITY
Ā
For many data-focused initiatives to be considered successful, they require improved documented understanding of the organizationās data.Ā Improvements in data understanding require accountability for the actions of putting clear definition behind your organizationās most valuable data. It makes sense that this process and associated metadata are governed.
In this monthās installment of the Real-World Data Governance webinar series, Bob Seiner will speak about how to focus your data governance program on improving the understanding of your organizationās data. Bob will talk about the data governance roles and processes required to improve the understanding of data and maintain the documented definitions.
In the webinar Bob will discuss:
Metadata associated with improving the understanding of data
How to select the appropriate metadata to improve understanding
Selecting processes to govern associated with improving data understanding
How improved understanding leads to improvements in project ROI
Measuring data understanding to demonstrate governance performance
RWDG: Data Governance and Three Levels of MetadataĀ DATAVERSITY
Ā
There are three levels of metadata that every organization must focus on. The three levels are the semantic level, the business level and the technical level. All three levels are important components of data governance and must be stewarded to focus on the goals and scope of your data governance program.
In this monthās installment of the Real-World Data Governance webinar series, Bob Seiner will present a three-tiered approach to defining, producing and using all levels of metadata to further the cause of data governance. Governing the processes associated with this metadata tends to be a central focus of successful data governance programs. Join Bob to learn how to simplify the metadata focus.
In this webinar Bob will discuss:
- The three levels of metadata and how they differ
- Sources of the metadata at each level
- Metadata linkage between the levels
- Processes to govern the all levels of metadata
- Institutionalizing policy to assure quality metadata at all levels
Business Value Metrics for Data GovernanceDATAVERSITY
Ā
This document discusses how to quantify and communicate the business value of data governance initiatives. It begins with background on information capability and data maturity levels. It then discusses frameworks for understanding business value, such as key performance indicators and how initiatives can generate revenue, cost savings or avoidance. The document provides examples of how to calculate return on investment, net present value and payback period to quantify benefits. It also discusses how to effectively communicate a business case by aligning it with organizational objectives and knowing your audience.
RWDG Slides: Data Governance and Three Levels of Metadata ManagementDATAVERSITY
Ā
There are three levels of metadata that every organization must govern well. These levels are the semantic level, the business level, and the technical level. All three levels are important components of Data Governance and must be stewarded to focus on the goals and scope of your Data Governance program.
In this monthās installment of the Real-World Data Governance webinar series, Bob Seiner will present a three-tiered approach to defining, producing, and using all levels of metadata to further the cause of Data Governance. Governing the processes associated with this metadata tends to be a central focus of successful Data Governance programs. Join Bob to learn how to simplify the metadata focus.
In this webinar, Bob will discuss:
ā¢ The three levels of metadata and how they differ
ā¢ Sources of the metadata at each level
ā¢ Metadata linkage between the levels
ā¢ Processes to govern all the levels of metadata
ā¢ Institutionalizing policy to assure quality metadata at all levels
RWDG Webinar: Build Your Own Data Governance ToolsDATAVERSITY
Ā
<!-- wp:paragraph -->
<p>Data Governance tools can be enablers of program successā¦or the reason why Data Governance fails to meet peopleās expectations. Software tools can be leveraged or acquired from reliable vendors or developed internally to attempt to address your organizationās needs. Sometimes the best environment is made up of a combination of internal and external tools. What is a practitioner to do?</p>
<!-- /wp:paragraph -->
<!-- wp:paragraph -->
<p>Join Bob Seiner for this monthās RWDG webinar where he will share tools that you can build yourself and talk about how the tools can be used to determine requirements to acquire outside tools. Tools developed internally at little or no cost have helped to solve many Data Governance problems. Several of these problems and their solutions will be described in detail during this webinar.</p>
<!-- /wp:paragraph -->
<!-- wp:paragraph -->
<p>In this webinar, Bob will discuss:</p>
<!-- /wp:paragraph -->
<!-- wp:list -->
<ul><li>Several easy to build Data Governance tools</li><li>Customizing these tools to address specific issues</li><li>How internally developed tools can lead to tool acquisition</li><li>Knowing when it is time to acquire tools</li><li>Integrating DIY tools with acquired tools</li></ul>
<!-- /wp:list -->
RWDG Slides: Building Data Governance Through Data StewardshipDATAVERSITY
Ā
Data stewards play an important role in Data Governance solutions. That is why it is critical that organizations get data stewardship right when setting up their program. The data is governed by people. Some people will even tell you that the discipline should be called people governance.
Bob Seiner has a lot to say on this subject. In this RWDG webinar, Bob shares the reasons why you must build your Data Governance program through the stewardship of the data. There is no governance without formal accountability for data. People become stewards when their relationship to data is formalized. It is the only way.
This webinar will focus on:
ā¢ The definition of data stewardship that MUST be adopted
ā¢ The critical role stewardship plays in governing data
ā¢ What it means to formalize accountability
ā¢ Why everybody in the organization is a data steward
ā¢ How to build Data Governance through stewardship
Good data is like good water: best served fresh, and ideally well-filtered. Data Management strategies can produce tremendous procedural improvements and increased profit margins across the board, but only if the data being managed is of a high quality. Determining how Data Quality should be engineered provides a useful framework for utilizing Data Quality management effectively in support of business strategy, which in turns allows for speedy identification of business problems, delineation between structural and practice-oriented defects in Data Management, and proactive prevention of future issues.
Over the course of this webinar, we will:
Help you understand foundational Data Quality concepts based on āThe DAMA Guide to the Data Management Body of Knowledgeā (DAMA DMBOK), as well as guiding principles, best practices, and steps for improving Data Quality at your organization
Demonstrate how chronic business challenges for organizations are often rooted in poor Data Quality
Share case studies illustrating the hallmarks and benefits of Data Quality success
DataEd Slides: Approaching Data Governance StrategicallyDATAVERSITY
Ā
At its core, Data Governance (DG) is: managing data with guidance. This immediately provokes the question: Would you tolerate your data managed without guidance? (In all likelihood, your organization has been managing data without adequate guidance and this accounts for its current, less-than-optimal state.) This program provides a practical guide to implementing DG or recharging your existing program. It provides your organization with an understanding of what Data Governance functions are required and how they fit with other Data Management disciplines. Understanding these aspects is a necessary prerequisite to eliminate the ambiguity that often surrounds initial discussions and implement effective Data Governance/Stewardship programs that manage data in support of organizational strategy. Program learning objectives include:
ā¢ Understanding why Data Governance can be tricky for organizations due to dataās confounding characteristics
ā¢ Strategy No. 1: Keeping DG practically focused
ā¢ Strategy No. 2: DG must exist at the same level as HR
ā¢ Strategy No. 3: Gradually add ingredients
ā¢ Data Governance in action: storytelling
Trends in Enterprise Advanced AnalyticsDATAVERSITY
Ā
This document summarizes trends in enterprise analytics presented by William McKnight. It discusses the increasing importance of data and analytics for businesses. Key trends include greater use of data lakes, multi-cloud strategies, master data management, data virtualization, graph databases, stream processing, self-service analytics, and the rise of roles like Chief Data Officer. Data science and analytics skills will become more operational. Selection of big data platforms will consider factors like SQL support, data size, and workload complexity. Overall, data maturity correlates strongly with business success and organizations must continually advance to remain competitive.
In order to find value in your organizationās data assets, heroic Data Stewards are tasked with saving the dayāevery single day! These heroes adhere to a Data Governance framework and work to ensure that data is captured right the first time, validated through automated means, and integrated into business processes. Whether itās data profiling or in-depth root cause analysis, Data Stewards can be counted on to ensure the organizationās mission-critical data is reliable. In this webinar, we will approach this framework and punctuate important facets of a Data Stewardās role.
- Understand the business need for a Data Governance framework
- Learn why embedded Data Quality principles are an important part of system/process design
- Identify opportunities to help drive your organization to a data-driven culture
Data Governance and Metadata ManagementDATAVERSITY
Ā
Metadata is a tool that improves data understanding, builds end-user confidence, and improves the return on investment in every asset associated with becoming a data-centric organization. Metadataās use has expanded beyond ādata about dataā to cover every phase of data analytics, protection, and quality improvement. Data Governance and metadata are connected at the hip in every way possible. As the song goes, āYou canāt have one without the other.ā
In this RWDG webinar, Bob Seiner will provide a way to renew your energy by focusing on the valuable asset that can make or break your Data Governance programās success. The truth is metadata is already inherent in your data environment, and it can be leveraged by making it available to all levels of the organization. At issue is finding the most appropriate ways to leverage and share metadata to improve data value and protection.
Throughout this webinar, Bob will share information about:
- Delivering an improved definition of metadata
- Communicating the relationship between successful governance and metadata
- Getting your business community to embrace the need for metadata
- Determining the metadata that will provide the most bang for your bucks
- The importance of Metadata Management to becoming data-centric
Data Architecture - The Foundation for Enterprise Architecture and GovernanceDATAVERSITY
Ā
Organizations are faced with an increasingly complex data landscape, finding themselves unable to cope with exponentially increasing data volumes, compounded by additional regulatory requirements with increased fines for non-compliance. Enterprise architecture and data governance are often discussed at length, but often with different stakeholder audiences. This can result in complementary and sometimes conflicting initiatives rather than a focused, integrated approach. Data governance requires a solid data architecture foundation in order to support the pillars of enterprise architecture. In this session, IDERAās Ron Huizenga will discuss a practical, integrated approach to effectively understand, define and implement an cohesive enterprise architecture and data governance discipline with integrated modeling and metadata management.
Strategic imperative the enterprise data modelDATAVERSITY
Ā
With today's increasingly complex data ecosystems, the Enterprise Data Model (EDM) is a strategic imperative that every organization should adopt. An Enterprise Data Model provides context and consistency for all organizational data assets, as well as a classification framework for data governance. Enterprise modeling is also totally consistent with agile workflows, evolving incrementally to keep pace with changing organizational factors. In this session, IDERAās Ron Huizenga will discuss the increasing importance of the EDM, how it serves as a framework for all enterprise data assets, and provides a foundation for data governance.
The first step toward understanding what data assets mean for your organization is understanding what those assets mean for each other. Metadataāliterally, data about dataāis one of many Data Management disciplines inherent in good systems development and is perhaps the most mislabeled and misunderstood of the lot. Understanding metadata and its associated technologies as more than just straightforward technological tools can provide powerful insight into the efficiency of organizational practices and can also enable you to combine more sophisticated Data Management techniques in support of larger and more complex business initiatives.In this webinar, we will:Illustrate how to leverage Metadata Management in support of your business strategyDiscuss foundational metadata concepts based on the DAMA Guide to Data Management Book of Knowledge (DAMA DMBOK)Enumerate guiding principles for and lessons previously learned from metadata and its practical uses
RWDG Slides: A Complete Set of Data Governance Roles & ResponsibilitiesDATAVERSITY
Ā
The document discusses roles and responsibilities in data governance. It describes five levels of roles - executive, strategic, tactical, operational, and support. For each level, it provides examples of common roles and discusses customizing roles to an organization's structure. The webinar will cover defining roles at each level, who participates, and detailed responsibilities. It emphasizes starting with existing roles and terminology.
RWDG Slides: Build an Effective Data Governance FrameworkDATAVERSITY
Ā
Data Governance frameworks are used to structure the core components of a Data Governance program. Frameworks add significant value for those organizations getting started and improve or address missing components for programs already in place.
This monthās RWDG webinar with Bob Seiner will focus on dissecting a common Data Governance framework and customizing the framework to match the needs of your organization. Frameworks can be complex to describe but, in this case, the framework will become the self-describing face of your program.
In this webinar, Bob will share:
- A customizable Data Governance framework
- Five core components of a Data Governance framework
- Five perspectives for addressing each component
- Using a framework to select an approach to Data Governance
- Detailed descriptions of each component from each perspective
ADV Slides: What Happened of Note in 1H 2020 in Enterprise Advanced AnalyticsDATAVERSITY
Ā
Reassessing the information management marketplace for your enterprise direction on an annual basis is too infrequent. The technology is changing too fast. Data and analytic maturity levels rapidly evolve. What is advanced today may be entry-level in two years. Letās look at the high points for 1H 2020 in information management developments and how that may change what you are doing now. This can also be a strong data point for preparing 2021 budgets.
This document discusses governing master data. It defines key terms like data governance and data stewardship. It explains the connection between master data and data governance, and why master data needs to be governed. It discusses applying governance roles and responsibilities to master data processes. Finally, it concludes that master data governance is focusing a data governance program on improving an organization's master data.
RWDG Webinar: Agile Data Governance - How to Apply Governance to AgileDATAVERSITY
Ā
Agile development efforts and Data Governance efforts are at odds with each other. Even though they both have the sponsorship at the highest level of the organization, there is disconnect when it comes to understanding how the two disciplines interact. Supporters of both disciplines swear by their trade and leave little wiggle room when it comes to working together. Organizations want FAST and they require ACCURATE DATA. Organizations require both.
Bob Seiner will address Agile Data Governance in this monthās installment of the Real-World Data Governance webinar series. Agile efforts are typically corporate priority efforts. Data as an asset is an integral corporate priority. Both disciplines are here to stay to address rapidly changing business requirements and improved analytical and data protection capabilities. Organizations must address this separation and they must act quickly.
This webinar will focus on:
ā¢Relating the Disciplines for Senior Leadership
ā¢Finding Common Ground between Agile and Data Governance
ā¢Applying Data Governance to Agile Efforts
ā¢Best Practices for Agile Data Governance
ā¢Gaining Agile Support for Data Activities
Everybody is a Data Steward ā Get Over It!DATAVERSITY
Ā
When Data Stewardship is based on peopleās relationships to data, the program is assured to cover the entire organization. People that define, produce, and use data must be held formally accountable for their actions. That may include every person in your organization. Is this a good thing? Of course, it is.
Join Bob Seiner for this monthās installment of his Real-World Data Governance webinar series, where he will share how formalizing accountability, based on the actions people take with data, requires heightened awareness and enforcement of data rules. These rules focus on improving Data Quality, protecting sensitive data, and increasing peopleās knowledge of the data that adds value for their business.
In this webinar, Bob will discuss:
Why the āEverybody is a Data Stewardā approach is different (and better)
How to recognize the Data Stewards
Formalizing accountability based on data relationships
Coverage of the entire organization
Leveraging the technique to sell stewardship
Slides: Accelerate and Assure the Adoption of Cloud Data Platforms Using Inte...DATAVERSITY
Ā
Greater agility, scalability, and lower total cost of ownership made the decision to move key elements of your organizationās data capability to the cloud easy. The real challenge is migrating data from your legacy systems to your new cloud platform so you can unleash its potential and value while minimizing the migration risks.
Combining erwinās data modeling, governance, and intelligence solutions with Snowflakeās modern cloud data platform, organizations can realize a scalable, governed, and transparent enterprise data capability.
In this session, weāll show you how enterprise stakeholders with different skills and needs can work together to accelerate and assure the success of cloud migration projects of any size. Youāll learn how to:
ā¢ Reduce costs and mitigate risks when migrating legacy applications to Snowflake with erwinās model-driven schema design and transformation capabilities
ā¢ Increase the precision, speed, and agility of Snowflake deployments with erwin data automation
ā¢ Assure transparency, compliance, and governance for Snowflake data and processes
ā¢ Increase the efficiency and accuracy of analytics and other data usage on the Snowflake Cloud Platform
RWDG Webinar: DIY and Purchased Data Governance ToolsDATAVERSITY
Ā
Data Governance tools are enablers to program success. The metadata stored in these tools become the backbone of a successful Data Governance program. The question of whether to build your own Data Governance tools versus purchasing Data Governance tools must be answered early in the program development process. There are benefits and drawbacks to either way you answer this question.
This monthās RWDG webinar with Bob Seiner focuses on making smart choices when it comes to selecting or developing the tools to support your Data Governance program. Bob will share his experiences of evaluating tools on the market and also share templates and tools that he has created to assist programs through the growing pains of success. There is something in the webinar for newbies and experienced practitioners.
In this webinar Bob will address:
ā¢ How to answer the Build vs Buy question
ā¢ Criteria for evaluating tools on the market
ā¢ Examples of tools you can create yourself
ā¢ Complimentary nature of DIY and purchased tools
ā¢ Cost and benefits of Data Governance tool choices
RWDG Webinar: Using Data Governance to Improve Data UnderstandingDATAVERSITY
Ā
For many data-focused initiatives to be considered successful, they require improved documented understanding of the organizationās data.Ā Improvements in data understanding require accountability for the actions of putting clear definition behind your organizationās most valuable data. It makes sense that this process and associated metadata are governed.
In this monthās installment of the Real-World Data Governance webinar series, Bob Seiner will speak about how to focus your data governance program on improving the understanding of your organizationās data. Bob will talk about the data governance roles and processes required to improve the understanding of data and maintain the documented definitions.
In the webinar Bob will discuss:
Metadata associated with improving the understanding of data
How to select the appropriate metadata to improve understanding
Selecting processes to govern associated with improving data understanding
How improved understanding leads to improvements in project ROI
Measuring data understanding to demonstrate governance performance
RWDG: Data Governance and Three Levels of MetadataĀ DATAVERSITY
Ā
There are three levels of metadata that every organization must focus on. The three levels are the semantic level, the business level and the technical level. All three levels are important components of data governance and must be stewarded to focus on the goals and scope of your data governance program.
In this monthās installment of the Real-World Data Governance webinar series, Bob Seiner will present a three-tiered approach to defining, producing and using all levels of metadata to further the cause of data governance. Governing the processes associated with this metadata tends to be a central focus of successful data governance programs. Join Bob to learn how to simplify the metadata focus.
In this webinar Bob will discuss:
- The three levels of metadata and how they differ
- Sources of the metadata at each level
- Metadata linkage between the levels
- Processes to govern the all levels of metadata
- Institutionalizing policy to assure quality metadata at all levels
RWDG Slides: Governing Your Data Catalog, Business Glossary, and Data DictionaryDATAVERSITY
Ā
The document discusses governing data catalogs, business glossaries, and data dictionaries. It describes these tools as core components of a successful data governance program and important at the operational and tactical levels. Governing the metadata in these tools provides value, but requires effort to govern roles, processes, communications, and metrics around these tools. The document advocates a pragmatic approach to governance through these tools to guide participation and knowledge sharing in a community.
The Role of Metadata in a Data Governance ProgramDATAVERSITY
Ā
1) Metadata is defined as data recorded in IT tools that improves the business and technical understanding of data and data-related assets.
2) There are three actions people take with data: define, produce, and use data. Metadata helps improve these actions.
3) Metadata needs governance roles at the executive, strategic, tactical, and operational levels to ensure its quality and usability.
Metadata Governance for Vocabularies, Dictionaries, and DataDATAVERSITY
Ā
This document summarizes a webinar on metadata governance for vocabularies, dictionaries, and data. The webinar discussed the value of metadata resources like business glossaries, data dictionaries, and data catalogs, and examined the metadata that populates each. It also covered responsibilities for governing metadata, applying governance to metadata processes, and requirements for tools to assist with metadata governance. The webinar aimed to help participants understand metadata governance and its differences from and relationships to data governance.
Real-World Data Governance Webinar: Using Data Governance to Achieve Data Qua...DATAVERSITY
Ā
Data Governance programs can focus on improving the quality of data. Improvements in quality require that people are held formally accountable for following defined processes for defining, producing and using data across the organization. These processes become the focal point of institutionalizing data quality.
In this monthās installment of the Real-World Data Governance webinar series, Bob Seiner will speak about how to focus your data governance program on improving the quality of data across the organization. Bob will talk about the data governance roles and processes required change organizational behavior associated with defining, producing and using quality data.
In the webinar Bob will discuss:
Defining data governance in terms of data quality
Delivering roles appropriate for improving data quality
Selecting appropriate data quality processes to govern
Using working groups to focus on data quality projects
Measuring quality to demonstrate governance performance
Driving Data Intelligence in the Supply Chain Through the Data Catalog at TJXDATAVERSITY
Ā
Roles and responsibilities are a critical component of every Data Governance program. Building a set of roles that are practical and that will not interfere with peopleās āday jobsā is an important consideration that will influence how well your program is adopted. This tutorial focuses on sharing a proven model guaranteed to represent your organization.
Join Bob Seiner for this lively webinar where he will dissect a complete Operating Model of Roles and Responsibilities that encompasses all levels of the organization. Seiner will detail the roles and describe the most effective way to associate people with the roles. You will walk out of this webinar with a model to apply to your organization.
In this session Bob will share:
- The five levels of Data Governance roles
- A proven Operating Model of Roles and Responsibilities
- How to customize the model to meet your requirements
- Setting appropriate role expectations
- How to operationalize the roles and demonstrate value
Are you spending your summer down by the Data Lake? If so, then you want to make certain that the lake is clean and that you pick the best place to swim. The Data Lake is the new analytical paradise that many organizations are banking on to become that answer to improved insights. And you need to prevent the lake from turning swampy.
In this monthās RWDG webinar, Bob Seiner and a special guest will focus on how to govern the data in your Data Lake. Bobās interaction with his guests is always lively, fact filled and this month they will help you to successfully swim through major barriers to provide an effective and valuable data resource.
In this webinar, Bob and his guest will discuss:
- The relationship between Data Lakes and Data Governance
- Preventing your Data Lake from becoming a Data Swamp
- Governing the Metadata associated with your Data Lake
- Leveraging governed data to provide trustworthy Analytics
- Measuring the value of a governed Data Lake
RWDG Slides: Stay Non-Invasive in Your Data Governance ApproachDATAVERSITY
Ā
There are three distinct approaches to implement Data Governance. The Command-and-Control Approach, the Traditional (if you build it they will come) Approach and the Non-Invasive Data Governance Approach. Some organizations select a single approach for their program while others select to follow a hybrid method.
Bob Seiner will provide information about each approach and indicate how the Non-Invasive Approach can follow the path of least resistance with the greatest success. You may be surprised to learn that many of your present activities can be leveraged to address Stewardship, Metadata, and governed processes ā all directed at staying as non-invasive as possible.
In this webinar, Bob will discuss:
- A Data Governance framework completed in a Non-Invasive way
- How the three approaches differ and when to use each
- Sticking to a single approach versus implementing a hybrid model
- How to sell Data Governance as something you are already doing
- Using the Non-Invasive Approach to win friends and influence people.
Real-World Data Governance: Metadata to Empower Data Stewards - Introducing t...DATAVERSITY
Ā
Metadata is the most valuable tool of the Data Steward. Where the stewards get their metadata and how they participate in the process of delivering core metadata is an issue organizations have been struggling with for years. The Operational Metadata Store or OMS may be the answer.
The traditional Operational Data Store or ODS is a database designed to integrate data from numerous sources that supports business operations and then feeds that data back into the operational systems. This Real-World Data Governance webinar with Bob Seiner and a panel of industry pundits will hold a lively discussion on the practicality of creating the ODS using metadata as the data, utilizing the metadata from a variety of existing sources to operationalize your data stewards.
The session will focus on:
Identifying the most significant metadata for your organization
Identifying existing sources of metadata ā known and hidden
Identifying when that metadata will be most useful to your data stewards
Defining a lifecycle that encourages data steward participation
Delivering a model that incorporates all of the above
Activate Data Governance Using the Data CatalogDATAVERSITY
Ā
This document discusses activating data governance using a data catalog. It compares active vs passive data governance, with active embedding governance into people's work through a catalog. The catalog plays a key role by allowing stewards to document definition, production, and usage of data in a centralized place. For governance to be effective, metadata from various sources must be consolidated and maintained in the catalog.
Metadata turns data into information by providing context. Metadata is a determining factor of a successful Data Governance initiative and becomes an important asset that needs to be managed. The metadata will not govern itself.
Join Bob Seiner for a webinar that focuses on the governance of metadata following the non-invasive approach. In this session, Bob will share tips and techniques for assuring that the appropriate metadata is being collected and utilized to support your Data Governance program.
In this webinar, Bob will discuss:
Concepts of Non-Invasive Metadata Governance
Metadata as a valuable data resource
Aligning Data Governance with Metadata Governance
Implementing effective Metadata Governance tools
Maximizing metadata resources with accountability
RWDG: Measuring Data Governance PerformanceDATAVERSITY
Ā
This document discusses ways to measure the performance of a data governance program. It describes measuring the acceptability of the program within the organization, such as the number of groups participating and customer satisfaction. It also describes measuring the business value of the program, like improvements in data documentation, understanding, quality and protection. The document provides examples of specific metrics that can be used, such as the number of critical data elements standardized or dollars saved/earned due to governance. It also discusses reporting metrics at different levels of a data governance framework.
RWDG Webinar: Big Data & BI Analytics Require Data GovernanceDATAVERSITY
Ā
Business Intelligence (BI) used to be equated to Data Warehousing. In this day of Big Data and improved analytical technologies and capabilities, BI now means a lot more. Where governing data in the data warehouse was a challenge ā governing the volume of Big Data in variable formats coming at us from all directions at a high velocity to maximize its analytical value has become paramount to differentiating an organization from its competition.
Join Bob Seiner for a Real-World Data Governance webinar focused on strengthening the relationship between Data Governance and corporate Big Data & Business Intelligence initiatives. This session will focus on expanding existing programs to address the expanding needs of the organization and building new programs to address the broadened definition of BI.
This webinar will cover:
Existing Governance Applications for BI
Future of Big Data & BI Data
Relationship between Big Data, BI and Governance
Articulating Governance Value in Terms of BI
True Intelligence Derived from Governed Data
RWDG Slides: Utilize Governance Working Teams to Improve Data QualityDATAVERSITY
Ā
Data Governance working teams are typically formed with a specific purpose or function in mind. Teams are deployed to address enterprise-wide data issues, business function issues and operational issues. These teams are made up of the ārightā people to solve the ārightā problem at the ārightā time. It is that easy. Or is it?
In this monthās RWDG webinar, Bob Seiner will share his experiences building working teams to improve how data is governed. Bob will talk about setting up the teams, ways to get resources to commit their time, and how to leverage their participation in a non-invasive manner.
In this webinar, Bob will discuss:
- When to make use of working teams
- How to construct a working team for a specific purpose
- Differences between working teams and communities of interest
- Monitoring and reporting on working team status
- How to deliver successful and repeatable problem-solving teams
Using Data Governance to Protect Sensitive DataDATAVERSITY
Ā
Many Data Governance programs start out by focusing on the protection of sensitive data. Improvements in protection of data require that people are held formally accountable for following the rules associated with appropriate handling of sensitive data. Communications and awareness of data classification and data handling processes become the focus of keeping data private.
In this monthās installment of the Real-World Data Governance webinar series, Bob Seiner will speak about how to focus your data governance program on protecting sensitive data. Bob will talk about the data governance roles and processes required to classify data and enforce the rules associated with protecting sensitive data. It may be less complicated than you think.
In the webinar Bob will discuss:
Tips and techniques for classifying data and defining data handling rules
Delivering roles appropriate for protecting sensitive data
Selecting appropriate data sharing processes to govern
Incremental implementation to protect the entire organization
Measuring protection to demonstrate governance performance
Glossaries, Dictionaries, and Catalogs Result in Data GovernanceDATAVERSITY
Ā
Data catalogs, business glossaries, and data dictionaries house metadata that is important to your organizationās governance of data. People in your organization need to be engaged in leveraging the tools, understanding the data that is available, who is responsible for the data, and knowing how to get their hands on the data to perform their job function. The metadata will not govern itself.
Join Bob Seiner for the webinar where he will discuss how glossaries, dictionaries, and catalogs can result in effective Data Governance. People must have confidence in the metadata associated with the data that you need them to trust. Therefore, the metadata in your data catalog, business glossary, and data dictionary must result in governed data. Learn how glossaries, dictionaries, and catalogs can result in Data Governance in this webinar.
Bob will discuss the following subjects in this webinar:
- Successful Data Governance relies on value from very important tools
- What it means to govern your data catalog, business glossary, and data dictionary
- Why governing the metadata in these tools is important
- The roles necessary to govern these tools
- Governance expected from metadata in catalogs, glossaries, and dictionaries
To take a āready, aim, fireā tactic to implement Data Governance, many organizations assess themselves against industry best practices. The process is not difficult or time-consuming and can directly assure that your activities target your specific needs. Best practices are always a strong place to start.
Join Bob Seiner for this popular RWDG topic, where he will provide the information you need to set your program in the best possible direction. Bob will walk you through the steps of conducting an assessment and share with you a set of typical results from taking this action. You may be surprised at how easy it is to organize the assessment and may hear results that stimulate the actions that you need to take.
In this webinar, Bob will share:
- The value of performing a Data Governance best practice assessment
- A practical list of industry Data Governance best practices
- Criteria to determine if a practice is best practice
- Steps to follow to complete an assessment
- Typical recommendations and actions that result from an assessment
RWDG Webinar: Metadata to Support Data GovernanceDATAVERSITY
Ā
This document describes a webinar on using metadata to support data governance. It provides definitions of key terms like data governance, metadata, and non-invasive data governance. It explains that metadata is a byproduct of good governance practices like formalizing accountability and standards. The webinar will cover selecting important initial metadata, using metadata to support the governance program, and incorporating governance into processes to manage metadata. It promotes integrating governance roles and responsibilities into existing methodologies.
Data Management, Metadata Management, and Data Governance ā Working TogetherDATAVERSITY
Ā
The data disciplines listed in the title must work together. The key to success requires understanding the boundaries and overlaps between the disciplines. Wouldnāt it be great to be able to present the relationships between the disciplines in a simple all-in diagram? At the end of this webinar, you will be able to do just that.
This new RWDG webinar with Bob Seiner will outline how Data Management, Metadata Management, and Data Governance can be optimized to work together. Bob will share a diagram that has successfully communicated the relationship between these disciplines to leadership resulting in the disciplines working in harmony and delivering success.
Bob will share the following in this webinar:
- Categories of disciplines focused on managing data as an asset
- A definition of Data Management that embraces numerous data disciplines
- The importance of Metadata -Management to all data disciplines
- Why data and metadata require formal governance
- A graphic that effectively exhibits the relationship between the disciplines
Similar to RWDG Slides: Metadata Governance for Catalogs, Glossaries, Dictionaries, and Data (20)
Architecture, Products, and Total Cost of Ownership of the Leading Machine Le...DATAVERSITY
Ā
Organizations today need a broad set of enterprise data cloud services with key data functionality to modernize applications and utilize machine learning. They need a comprehensive platform designed to address multi-faceted needs by offering multi-function data management and analytics to solve the enterpriseās most pressing data and analytic challenges in a streamlined fashion.
In this research-based session, Iāll discuss what the components are in multiple modern enterprise analytics stacks (i.e., dedicated compute, storage, data integration, streaming, etc.) and focus on total cost of ownership.
A complete machine learning infrastructure cost for the first modern use case at a midsize to large enterprise will be anywhere from $3 million to $22 million. Get this data point as you take the next steps on your journey into the highest spend and return item for most companies in the next several years.
Data at the Speed of Business with Data Mastering and GovernanceDATAVERSITY
Ā
Do you ever wonder how data-driven organizations fuel analytics, improve customer experience, and accelerate business productivity? They are successful by governing and mastering dataĀ effectively so they can get trusted data to those who need it faster.Ā Efficient dataĀ discovery,Ā masteringĀ andĀ democratizationĀ is critical for swiftly linking accurate data with business consumers.Ā When business teams can quickly and easily locate, interpret, trust, and apply data assets to support sound business judgment, it takes less time to see value.Ā
Ā
Join data mastering and data governanceĀ experts from Informaticaāplus a real-world organization empowering trusted data for analyticsāfor a livelyĀ panelĀ discussion. Youāll hear more aboutĀ how a single cloud-native approach can help global businesses in any economy create more valueāfaster, more reliably, and with more confidenceāby making data management and governance easier to implement.
What is data literacy? Which organizations, and which workers in those organizations, need to be data-literate? There are seemingly hundreds of definitions of data literacy, along with almost as many opinions about how to achieve it.Ā Ā Ā
In a broader perspective, companies must consider whether data literacy is an isolated goal or one component of a broader learning strategy to address skill deficits. How does data literacy compare to other types of skills or āliteracyā such as business acumen?Ā
This session will position data literacy in the context of other worker skills as a framework for understanding how and where it fits and how to advocate for its importance.
Building a Data Strategy ā Practical Steps for Aligning with Business GoalsDATAVERSITY
Ā
Developing a Data Strategy for your organization can seem like a daunting task ā but itās worth the effort. Getting your Data Strategy right can provide significant value, as data drives many of the key initiatives in todayās marketplace ā from digital transformation, to marketing, to customer centricity, to population health, and more. This webinar will help demystify Data Strategy and its relationship to Data Architecture and will provide concrete, practical ways to get started.
Uncover how your business can save money and find new revenue streams.
Driving profitability is a top priority for companies globally, especially in uncertain economic times. It's imperative that companies reimagine growth strategies and improve process efficiencies to help cut costs and drive revenue ā but how?
By leveraging data-driven strategies layered with artificial intelligence, companies can achieve untapped potential and help their businesses save money and drive profitability.
In this webinar, you'll learn:
- How your company can leverage data and AI to reduce spending and costs
- Ways you can monetize data and AI and uncover new growth strategies
- How different companies have implemented these strategies to achieve cost optimization benefits
Data Catalogs Are the Answer ā What is the Question?DATAVERSITY
Ā
Organizations with governed metadata made available through their data catalog can answer questions their people have about the organizationās data. These organizations get more value from their data, protect their data better, gain improved ROI from data-centric projects and programs, and have more confidence in their most strategic data.
Join Bob Seiner for this lively webinar where he will talk about the value of a data catalog and how to build the use of the catalog into your stewardsā daily routines. Bob will share how the tool must be positioned for success and viewed as a must-have resource that is a steppingstone and catalyst to governed data across the organization.
Data Catalogs Are the Answer ā What Is the Question?DATAVERSITY
Ā
Organizations with governed metadata made available through their data catalog can answer questions their people have about the organizationās data. These organizations get more value from their data, protect their data better, gain improved ROI from data-centric projects and programs, and have more confidence in their most strategic data.
Join Bob Seiner for this lively webinar where he will talk about the value of a data catalog and how to build the use of the catalog into your stewardsā daily routines. Bob will share how the tool must be positioned for success and viewed as a must-have resource that is a steppingstone and catalyst to governed data across the organization.
In this webinar, Bob will focus on:
-Selecting the appropriate metadata to govern
-The business and technical value of a data catalog
-Building the catalog into peopleās routines
-Positioning the data catalog for success
-Questions the data catalog can answer
Because every organization produces and propagates data as part of their day-to-day operations, data trends are becoming more and more important in the mainstream business worldās consciousness. For many organizations in various industries, though, comprehension of this development begins and ends with buzzwords: āBig Data,ā āNoSQL,ā āData Scientist,ā and so on. Few realize that all solutions to their business problems, regardless of platform or relevant technology, rely to a critical extent on the data model supporting them. As such, data modeling is not an optional task for an organizationās data effort, but rather a vital activity that facilitates the solutions driving your business. Since quality engineering/architecture work products do not happen accidentally, the more your organization depends on automation, the more important the data models driving the engineering and architecture activities of your organization. This webinar illustrates data modeling as a key activity upon which so much technology and business investment depends.
Specific learning objectives include:
- Understanding what types of challenges require data modeling to be part of the solution
- How automation requires standardization on derivable via data modeling techniques
- Why only a working partnership between data and the business can produce useful outcomes
Analytics play a critical role in supporting strategic business initiatives. Despite the obvious value to analytic professionals of providing the analytics for these initiatives, many executives question the economic return of analytics as well as data lakes, machine learning, master data management, and the like.
Technology professionals need to calculate and present business value in terms business executives can understand. Unfortunately, most IT professionals lack the knowledge required to develop comprehensive cost-benefit analyses and return on investment (ROI) measurements.
This session provides a framework to help technology professionals research, measure, and present the economic value of a proposed or existing analytics initiative, no matter the form that the business benefit arises. The session will provide practical advice about how to calculate ROI and the formulas, and how to collect the necessary information.
How a Semantic Layer Makes Data Mesh Work at ScaleDATAVERSITY
Ā
Data Mesh is a trending approach to building a decentralized data architecture by leveraging a domain-oriented, self-service design. However, the pure definition of Data Mesh lacks a center of excellence or central data team and doesnāt address the need for a common approach for sharing data products across teams. The semantic layer is emerging as a key component to supporting a Hub and Spoke style of organizing data teams by introducing data model sharing, collaboration, and distributed ownership controls.
This session will explain how data teams can define common models and definitions with a semantic layer to decentralize analytics product creation using a Hub and Spoke architecture.
Attend this session to learn about:
- The role of a Data Mesh in the modern cloud architecture.
- How a semantic layer can serve as the binding agent to support decentralization.
- How to drive self service with consistency and control.
Enterprise data literacy. A worthy objective? Certainly! A realistic goal? That remains to be seen. As companies consider investing in data literacy education, questions arise about its value and purpose. While the destination ā having a data-fluent workforce ā is attractive, we wonder how (and if) we can get there. Ā Ā
Kicking off this webinar series, we begin with a panel discussion to explore the landscape of literacy, including expert positions and results from focus groups:
- why it matters,
- what it means,
- what gets in the way,
- who needs it (and how much they need),
- what companies believe it will accomplish.
In this engaging discussion about literacy, we will set the stage for future webinars to answer specific questions and feature successful literacy efforts.
The Data Trifecta ā Privacy, Security & Governance Race from Reactivity to Re...DATAVERSITY
Ā
Change is hard, especially in response to negative stimuli or what is perceived as negative stimuli. So organizations need to reframe how they think about data privacy, security and governance, treating them as value centers to 1) ensure enterprise data can flow where it needs to, 2) prevent ā not just react ā to internal and external threats, and 3) comply with data privacy and security regulations.
Working together, these roles can accelerate faster access to approved, relevant and higher quality data ā and that means more successful use cases, faster speed to insights, and better business outcomes. However, both new information and tools are required to make the shift from defense to offense, reducing data drama while increasing its value.
Join us for this panel discussion with experts in these fields as they discuss:
- Recent research about where data privacy, security and governance stand
- The most valuable enterprise data use cases
- The common obstacles to data value creation
- New approaches to data privacy, security and governance
- Their advice on how to shift from a reactive to resilient mindset/culture/organization
Youāll be educated, entertained and inspired by this panel and their expertise in using the data trifecta to innovate more often, operate more efficiently, and differentiate more strategically.
Emerging Trends in Data Architecture ā Whatās the Next Big Thing?DATAVERSITY
Ā
With technological innovation and change occurring at an ever-increasing rate, itās hard to keep track of whatās hype and what can provide practical value for your organization. Join this webinar to see the results of a recent DATAVERSITY survey on emerging trends in Data Architecture, along with practical commentary and advice from industry expert Donna Burbank.Ā
Data Governance Trends - A Look Backwards and ForwardsDATAVERSITY
Ā
As DATAVERSITYās RWDG series hurdles into our 12th year, this webinar takes a quick look behind us, evaluates the present, and predicts the future of Data Governance. Based on webinar numbers, hot Data Governance topics have evolved over the years from policies and best practices, roles and tools, data catalogs and frameworks, to supporting data mesh and fabric, artificial intelligence, virtualization, literacy, and metadata governance.Ā
Join Bob Seiner as he reflects on the past and what has and has not worked, while sharing examples of enterprise successes and struggles. In this webinar, Bob will challenge the audience to stay a step ahead by learning from the past and blazing a new trail into the future of Data Governance.Ā
In this webinar, Bob will focus on:Ā
- Data Governanceās past, present, and futureĀ
- How trials and tribulations evolve to successĀ
- Leveraging lessons learned to improve productivityĀ
- The great Data Governance tool explosionĀ
- The future of Data Governance
Data Governance Trends and Best Practices To Implement TodayDATAVERSITY
Ā
1) The document discusses best practices for data protection on Google Cloud, including setting data policies, governing access, classifying sensitive data, controlling access, encryption, secure collaboration, and incident response.
2) It provides examples of how to limit access to data and sensitive information, gain visibility into where sensitive data resides, encrypt data with customer-controlled keys, harden workloads, run workloads confidentially, collaborate securely with untrusted parties, and address cloud security incidents.
3) The key recommendations are to protect data at rest and in use through classification, access controls, encryption, confidential computing; securely share data through techniques like secure multi-party computation; and have an incident response plan to quickly address threats.
It is a fascinating, explosive time for enterprise analytics.
It is from the position of analytics leadership that the enterprise mission will be executed and company leadership will emerge. The data professional is absolutely sitting on the performance of the company in this information economy and has an obligation to demonstrate the possibilities and originate the architecture, data, and projects that will deliver analytics. After all, no matter what business youāre in, youāre in the business of analytics.
The coming years will be full of big changes in enterprise analytics and data architecture. William will kick off the fifth year of the Advanced Analytics series with a discussion of the trends winning organizations should build into their plans, expectations, vision, and awareness now.
Too often I hear the question āCan you help me with our data strategy?ā Unfortunately, for most, this is the wrong request because it focuses on the least valuable component: the data strategy itself. A more useful request is: āCan you help me apply data strategically?ā Yes, at early maturity phases the process of developing strategic thinking about data is more important than the actual product! Trying to write a good (must less perfect) data strategy on the first attempt is generally not productive āparticularly given the widespread acceptance of Mike Tysonās truism: āEverybody has a plan until they get punched in the face.ā This program refocuses efforts on learning how to iteratively improve the way data is strategically applied. This will permit data-based strategy components to keep up with agile, evolving organizational strategies. It also contributes to three primary organizational data goals.Ā Learn how to improve the following:
- Your organizationās data
- The way your people use data
- The way your people use data to achieve your organizational strategy
This will help in ways never imagined. Data are your sole non-depletable, non-degradable, durable strategic assets, and they are pervasively shared across every organizational area. Addressing existing challenges programmatically includes overcoming necessary but insufficient prerequisites and developing a disciplined, repeatable means of improving business objectives. This process (based on the theory of constraints) is where the strategic data work really occurs as organizations identify prioritized areas where better assets, literacy, and support (data strategy components) can help an organization better achieve specific strategic objectives. Then the process becomes lather, rinse, and repeat. Several complementary concepts are also covered, including:
- A cohesive argument for why data strategy is necessary for effective data governance
- An overview of prerequisites for effective strategic use of data strategy, as well as common pitfalls
- A repeatable process for identifying and removing data constraints
- The importance of balancing business operation and innovation
Who Should Own Data Governance ā IT or Business?DATAVERSITY
Ā
The question is asked all the time: āWhat part of the organization should own your Data Governance program?ā The typical answers are āthe businessā and āIT (information technology).ā Another answer to that question is āYes.ā The program must be owned and reside somewhere in the organization. You may ask yourself if there is a correct answer to the question.
Join this new RWDG webinar with Bob Seiner where Bob will answer the question that is the title of this webinar. Determining ownership of Data Governance is a vital first step. Figuring out the appropriate part of the organization to manage the program is an important second step. This webinar will help you address these questions and more.
In this session Bob will share:
- What is meant by āthe businessā when it comes to owning Data Governance
- Why some people say that Data Governance in IT is destined to fail
- Examples of IT positioned Data Governance success
- Considerations for answering the question in your organization
- The final answer to the question of who should own Data Governance
This document summarizes a research study that assessed the data management practices of 175 organizations between 2000-2006. The study had both descriptive and self-improvement goals, such as understanding the range of practices and determining areas for improvement. Researchers used a structured interview process to evaluate organizations across six data management processes based on a 5-level maturity model. The results provided insights into an organization's practices and a roadmap for enhancing data management.
MLOps ā Applying DevOps to Competitive AdvantageDATAVERSITY
Ā
MLOps is a practice for collaboration between Data Science and operations to manage the production machine learning (ML) lifecycles. As an amalgamation of āmachine learningā and āoperations,ā MLOps applies DevOps principles to ML delivery, enabling the delivery of ML-based innovation at scale to result in:
Faster time to market of ML-based solutions
More rapid rate of experimentation, driving innovation
Assurance of quality, trustworthiness, and ethical AI
MLOps is essential for scaling ML. Without it, enterprises risk struggling with costly overhead and stalled progress. Several vendors have emerged with offerings to support MLOps: the major offerings are Microsoft Azure ML and Google Vertex AI. We looked at these offerings from the perspective of enterprise features and time-to-value.
Interview Methods - Marital and Family Therapy and Counselling - Psychology S...PsychoTech Services
Ā
A proprietary approach developed by bringing together the best of learning theories from Psychology, design principles from the world of visualization, and pedagogical methods from over a decade of training experience, that enables you to: Learn better, faster!
This presentation is about health care analysis using sentiment analysis .
*this is very useful to students who are doing project on sentiment analysis
*
PyData London 2024: Mistakes were made (Dr. Rebecca Bilbro)Rebecca Bilbro
Ā
To honor ten years of PyData London, join Dr. Rebecca Bilbro as she takes us back in time to reflect on a little over ten years working as a data scientist. One of the many renegade PhDs who joined the fledgling field of data science of the 2010's, Rebecca will share lessons learned the hard way, often from watching data science projects go sideways and learning to fix broken things. Through the lens of these canon events, she'll identify some of the anti-patterns and red flags she's learned to steer around.
Essential Skills for Family Assessment - Marital and Family Therapy and Couns...PsychoTech Services
Ā
A proprietary approach developed by bringing together the best of learning theories from Psychology, design principles from the world of visualization, and pedagogical methods from over a decade of training experience, that enables you to: Learn better, faster!