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:
• How governance applies equally to data and metadata
• The meaning of a “resolute effort” to govern important assets
• How the governance of data and metadata increases their value
• The people who must be held formally accountable for data and metadata
• Communicating the webinar’s title with people who can make a difference
RWDG Slides: The Future of Data Governance – IoT, AI, IG, and CloudDATAVERSITY
Data Governance, as a discipline, has been around for more than 20 years. With each passing year, Data Governance faces new challenges that come from advances in technology and new ways of leveraging data to do business. The changes make life interesting for those of us delivering formalized Data Governance programs.
Join Bob Seiner for this month’s webinar focused on keeping Data Governance current with advancements in information technology and how to stay relevant as the uses of data expand around us. The data at the heart of each advancement will not govern itself. That is the future of Data Governance.
In this webinar, Bob will discuss:
• Advancements in Information Technology
• The impact of the advances on Data Governance
• The impact of Data Governance on the advances
• What the future of Data Governance looks like
• How to sell Data Governance’s role moving forward
RWDG Slides: Data Governance and Three Levels of Metadata ManagementDATAVERSITY
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 month’s 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 all the levels of metadata
• Institutionalizing policy to assure quality metadata at all levels
RWDG Slides: Master Data Governance in ActionDATAVERSITY
Master data is data essential to operations in a specific subject area. Information treated as master data varies from one subject to another and even from one company to another. However defined, one thing for certain is that it does not become master data unless it is governed.
Join Bob Seiner for this RWDG webinar where he outlines a repeatable way to activate your Data Governance program by focusing on your master data initiatives. Get people to trust your data as the “master” by implementing a formal certification process.
In this webinar, Bob will discuss:
• What makes it Master Data Governance
• Aligning roles and responsibilities with Master Data Management (MDM)
• Qualities of “governed data”
• Governing to a “master” version of the truth
• Implementing Data Governance domain by domain
RWDG Slides: Data Architecture Is Data GovernanceDATAVERSITY
Data Architecture and Data Governance are the same thing! Aren’t they?
Most people would say that this line of thinking is absurd — or even worse. There is NO WAY that they are the same thing. Or are they?
This RWDG webinar with Bob Seiner and his special guest Anthony Algmin looks at the disciplines of Data Governance and Data Architecture and explores how much they are the same … and how they are different. The speakers will let you draw your own conclusion, but they will get you thinking about whether Data Architecture and Data Governance are two sides of the same coin.
In this webinar, Bob and Anthony will discuss:
• What is meant by the saying two sides of the same coin … and how it relates
• The similarities between Data Architecture and Data Governance
• The differences between the two
• How to use Data Architecture to sell Data Governance … and the other way around
• Deciding if the two disciplines are the same … or different
Slides: The Three Pillars for Effective Business Intelligence GovernanceDATAVERSITY
Business intelligence (BI) governance can be intimidating for many large enterprises. Users have access to multiple tools and content, and establishing a uniform layer of governance on top of a heterogeneous environment is a daunting task. However, governance is critical, and the lack of proper governance leads to poor user engagement and low ROI from BI investments.
Metric Insights’ Business Intelligence Portal helps you:
• Manage information access and discoverability
• Optimize BI content, license utilization, and staff resources
• Create trust with your BI team and the content they produce
RWDG Slides: Glossaries, Dictionaries, and Catalogs Result in Data GovernanceDATAVERSITY
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 month’s 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:
• How glossaries, dictionaries, and catalogs add value
• What should be included in these assets
• Who has responsibility for these assets
• When these assets will be valuable to your organization
• Where the discipline results in Data Governance
DAS Slides: Building a Future-State Data Architecture Plan - Where to Begin?DATAVERSITY
This document summarizes a webinar on building a future-state data architecture. It discusses defining data management and identifying current and future hot technologies. Relational databases dominate currently while cloud adoption is increasing. Stakeholders beyond IT are increasingly involved in data decisions. The webinar also outlines key steps to create a data management program, including defining goals, identifying critical data, assessing maturity, and creating a roadmap. An effective roadmap balances business priorities and shows quick wins while building to long term goals.
If you define, produce, or use data as part of your job and you are held formally accountable for how you define, produce, and use the data, then you are a data steward. If that statement is true, then everybody is a data steward. Does this make your Data Governance program more complex?
Join Bob Seiner for this thought-provoking webinar that asks and answers the question, how can everybody be a data steward? His approach to Data Stewardship will at the same time make your program less invasive to deliver and add a touch of complexity when it is recognized that the governance of data involves everybody in the organization.
In this webinar, Bob will talk about:
- Defining the levels and roles of data stewards
- What the term “formalized accountability” means
- How to handle the complexity of everybody being a data steward
- The complete coverage that is deployed by this approach
- How to “get over” everybody being a data steward
RWDG Slides: The Future of Data Governance – IoT, AI, IG, and CloudDATAVERSITY
Data Governance, as a discipline, has been around for more than 20 years. With each passing year, Data Governance faces new challenges that come from advances in technology and new ways of leveraging data to do business. The changes make life interesting for those of us delivering formalized Data Governance programs.
Join Bob Seiner for this month’s webinar focused on keeping Data Governance current with advancements in information technology and how to stay relevant as the uses of data expand around us. The data at the heart of each advancement will not govern itself. That is the future of Data Governance.
In this webinar, Bob will discuss:
• Advancements in Information Technology
• The impact of the advances on Data Governance
• The impact of Data Governance on the advances
• What the future of Data Governance looks like
• How to sell Data Governance’s role moving forward
RWDG Slides: Data Governance and Three Levels of Metadata ManagementDATAVERSITY
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 month’s 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 all the levels of metadata
• Institutionalizing policy to assure quality metadata at all levels
RWDG Slides: Master Data Governance in ActionDATAVERSITY
Master data is data essential to operations in a specific subject area. Information treated as master data varies from one subject to another and even from one company to another. However defined, one thing for certain is that it does not become master data unless it is governed.
Join Bob Seiner for this RWDG webinar where he outlines a repeatable way to activate your Data Governance program by focusing on your master data initiatives. Get people to trust your data as the “master” by implementing a formal certification process.
In this webinar, Bob will discuss:
• What makes it Master Data Governance
• Aligning roles and responsibilities with Master Data Management (MDM)
• Qualities of “governed data”
• Governing to a “master” version of the truth
• Implementing Data Governance domain by domain
RWDG Slides: Data Architecture Is Data GovernanceDATAVERSITY
Data Architecture and Data Governance are the same thing! Aren’t they?
Most people would say that this line of thinking is absurd — or even worse. There is NO WAY that they are the same thing. Or are they?
This RWDG webinar with Bob Seiner and his special guest Anthony Algmin looks at the disciplines of Data Governance and Data Architecture and explores how much they are the same … and how they are different. The speakers will let you draw your own conclusion, but they will get you thinking about whether Data Architecture and Data Governance are two sides of the same coin.
In this webinar, Bob and Anthony will discuss:
• What is meant by the saying two sides of the same coin … and how it relates
• The similarities between Data Architecture and Data Governance
• The differences between the two
• How to use Data Architecture to sell Data Governance … and the other way around
• Deciding if the two disciplines are the same … or different
Slides: The Three Pillars for Effective Business Intelligence GovernanceDATAVERSITY
Business intelligence (BI) governance can be intimidating for many large enterprises. Users have access to multiple tools and content, and establishing a uniform layer of governance on top of a heterogeneous environment is a daunting task. However, governance is critical, and the lack of proper governance leads to poor user engagement and low ROI from BI investments.
Metric Insights’ Business Intelligence Portal helps you:
• Manage information access and discoverability
• Optimize BI content, license utilization, and staff resources
• Create trust with your BI team and the content they produce
RWDG Slides: Glossaries, Dictionaries, and Catalogs Result in Data GovernanceDATAVERSITY
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 month’s 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:
• How glossaries, dictionaries, and catalogs add value
• What should be included in these assets
• Who has responsibility for these assets
• When these assets will be valuable to your organization
• Where the discipline results in Data Governance
DAS Slides: Building a Future-State Data Architecture Plan - Where to Begin?DATAVERSITY
This document summarizes a webinar on building a future-state data architecture. It discusses defining data management and identifying current and future hot technologies. Relational databases dominate currently while cloud adoption is increasing. Stakeholders beyond IT are increasingly involved in data decisions. The webinar also outlines key steps to create a data management program, including defining goals, identifying critical data, assessing maturity, and creating a roadmap. An effective roadmap balances business priorities and shows quick wins while building to long term goals.
If you define, produce, or use data as part of your job and you are held formally accountable for how you define, produce, and use the data, then you are a data steward. If that statement is true, then everybody is a data steward. Does this make your Data Governance program more complex?
Join Bob Seiner for this thought-provoking webinar that asks and answers the question, how can everybody be a data steward? His approach to Data Stewardship will at the same time make your program less invasive to deliver and add a touch of complexity when it is recognized that the governance of data involves everybody in the organization.
In this webinar, Bob will talk about:
- Defining the levels and roles of data stewards
- What the term “formalized accountability” means
- How to handle the complexity of everybody being a data steward
- The complete coverage that is deployed by this approach
- How to “get over” everybody being a data steward
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 organization’s most important metadata.
Seiner dataversity-rwdg2017-05-operating modelofdatagovernanceroles-20170518f...DATAVERSITY
Roles and responsibilities are the foundation of a successful Data Governance program. An operating model of roles focuses on all levels of the organization including the executive, strategic, tactical and operational responsibilities. A complete model also includes roles that support the program.
In this month’s RWDG webinar, Bob Seiner will present a proven Operating Model of Data Governance Roles & Responsibilities that can be applied to the existing culture of any organization. This webinar may be the most important webinar of the year because of its impact on the rest of your data governance program.
In this webinar Bob will share information about:
The Operating Model as a pyramid diagram
Three different approaches to stewardship
Five distinct levels of responsibilities
Who is expected to participate at each level?
What will be “the ask” of these people?
RWDG Slides: What is a Data Steward to do?DATAVERSITY
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 month’s 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
Data Governance and Metadata ManagementDATAVERSITY
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. Metadata’s use has expanded beyond “data about data” 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, “You can’t have one without the other.”
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 program’s 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
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
Real-World Data Governance: Metadata to Empower Data Stewards - Introducing t...DATAVERSITY
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 – 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
This document provides an agenda and speaker bios for the "DAMA Turkey Chapter" event titled "Data Management: Where to Start?". The event will include presentations from the DAMA International President, the Teradata CTO, an ING Bank Senior Manager, a communication consultant, and a BI evangelist on topics related to data management best practices, effective communication for data managers, and practical data governance. It will take place on March 26, 2012 in Istanbul, Turkey.
Analyze This! Best Practices For Big And Fast DataEMC
During this recorded webcast, you will hear from Judith Hurwitz, noted analyst and author of Hybrid Cloud for Dummies and Bill Schmarzo, EMC Consulting’s CTO for EIMA. You will learn What is big fast data and how your organization will benefit from this transformation in data management.
This document provides an overview of portal governance and outlines an approach to establishing a portal governance framework. It defines portal governance as establishing the appropriate structures, roles, and processes to support efficient decision-making for managing a portal infrastructure and publishing new assets. It emphasizes that governance is important to coordinate the various stakeholder groups involved in a portal and prevent uncoordinated "organic" development. The document then outlines the initial steps to start a governance process, including defining what needs to be governed, how it will be governed, establishing governance teams and their roles and responsibilities, and growing and enforcing the governance over time.
Everybody is a Data Steward – Get Over It!DATAVERSITY
When Data Stewardship is based on people’s 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 month’s 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 people’s knowledge of the data that adds value for their business.
In this webinar, Bob will discuss:
Why the “Everybody is a Data Steward” 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: Knowledge Graphs vs. Property GraphsDATAVERSITY
We are in the era of graphs. Graphs are hot. Why? Flexibility is one strong driver: Heterogeneous data, integrating new data sources, and analytics all require flexibility. Graphs deliver it in spades.
Over the last few years, a number of new graph databases came to market. As we start the next decade, dare we say “the semantic twenties,” we also see vendors that never before mentioned graphs starting to position their products and solutions as graphs or graph-based.
Graph databases are one thing, but “Knowledge Graphs” are an even hotter topic. We are often asked to explain Knowledge Graphs.
Today, there are two main graph data models:
• Property Graphs (also known as Labeled Property Graphs)
• RDF Graphs (Resource Description Framework) aka Knowledge Graphs
Other graph data models are possible as well, but over 90 percent of the implementations use one of these two models. In this webinar, we will cover the following:
I. A brief overview of each of the two main graph models noted above
II. Differences in Terminology and Capabilities of these models
III. Strengths and Limitations of each approach
IV. Why Knowledge Graphs provide a strong foundation for Enterprise Data Governance and Metadata Management
Seiner dataversity - rwdg 2017-09 - how to select the appropriate data gove...DATAVERSITY
Organizations purchase Data Governance Tools to formalize responsibility and automate and assist the processes of governing data and metadata. There are many different types of tools on the market that assist in program implementation and there are several criteria and requirements that organization’s use to review and assess available tools.
In this installment of the RWDG webinar series, Bob Seiner will talk about the types of tools available on the market and requirements that can be used to assist in the selection of the most appropriate tool for your organization. Learn about the latest types of data governance tools and how to select the right one in this RWDG webinar.
Data Governance and the Internet of ThingsDATAVERSITY
Several years back there were already more devices connected to the internet than people. It is estimated that more than 20 billion devices will be connected by 2020 and that number will never fall. Connecting to the internet implies the transfer of data. The numbers of devices and what they transfer imply a lot of data. Who is governing all of this data?
Join Bob Seiner for this month’s installment of Real-World Data Governance to expand your appreciation of the data issues that pertain to the Internet of Things (IoT). You may be surprised how much of what you already know about data governance applies to governing this new definition, production and use of data.
In this webinar Bob will talk about:
•Clear Description of IoT Focused on the data
•Addressing Data Management Concerns
•Applications of IoT Data
•Dimensions of IoT Data Processes and Quality
•Risk Associated with Interoperability
This document provides a checklist report on modernizing data warehouse infrastructure. It discusses six key points regarding modernization: 1) Diversifying the portfolio of data platforms to satisfy modern data requirements, 2) Modernizing with cloud and hybrid strategies, 3) Modernizing hardware for greater speed, scale and lower costs, 4) Coordinating modernization with business and analytics modernization, 5) Adjusting data management practices to fit modern warehousing, and 6) Leveraging multi-vendor partnerships for a unified, high-performance infrastructure. The report emphasizes that modern warehouses require multiple data platform types to meet diverse needs, and that infrastructure modernization is driven by business demands for advanced analytics and self-service data practices.
Slides: Powering a Sustainable Data Governance Program – Learnings & Best Pra...DATAVERSITY
This document summarizes a presentation about E.ON Energy's data governance program. E.ON implemented a metadata management platform and data governance practices to address issues like limited data access, lack of a data catalog, and inefficient data usage. Initial results included defining data domains, connecting systems, training users, and standardizing reporting. The program aims to accelerate value from data, ensure compliance, demand trusted insights, and foster collaboration across the organization. Senior leaders must engage to support such initiatives, and building a data-driven culture is key to success.
Real-World Data Governance: Comparing World Class Solutions in Data Governanc...DATAVERSITY
This document outlines the agenda for a webinar on comparing world class data governance solutions. The webinar will feature a panel of practitioners discussing their approaches to data stewardship, metadata, and master data governance. The panelists include professionals from PNC Bank, the Church of Latter Day Saints, and the Data Governance Institute. The webinar will be moderated by Robert Seiner and cover identifying data stewards, handling metadata, governing master data, and taking questions from the audience.
RWDG Slides: Data Governance versus Information GovernanceDATAVERSITY
If Data Governance is the execution and enforcement of authority over the management of data and data-related assets, what is Information Governance? How are they the same and how do they differ? This is a question pondered by the greatest minds in Data Management. And there is no correct answer.
Join Bob Seiner for this month’s RWDG webinar where he will compare Data and Information Governance and share situations when it is makes sense to call it one over the other. Most organizations name their program after they select exactly what will be governed and how that governed “stuff” will be used. What are you governing?
In this webinar, Bob will discuss:
- Describing what it means to “Govern” something
- How to define Governance in both contexts
- Differences between Data and Information Governance
- How to select what to call your program
- Why what you call your program matters … or does it?
Enterprise Architecture vs. Data ArchitectureDATAVERSITY
Enterprise Architecture (EA) provides a visual blueprint of the organization, and shows key interrelationships between data, process, applications, and more. By abstracting these assets in a graphical view, it’s possible to see key interrelationships, particularly as they relate to data and its business impact across the organization. Join us for a discussion on how data architecture is a key component of an overall enterprise architecture for enhanced business value and success.
Real-World Data Governance: Build Your Own Data Governance ToolsDATAVERSITY
There are many tools available to assist your organization to govern your data better. The value from these tools is proven and organizations come to rely on using these tools to deliver high quality and protected data. Some of these tools are available for purchase however many can be developed and provided internally.
This RWDG webinar with Bob Seiner will address the design, development and deployment of several key instruments of data governance success. Bob will describe the purpose of these tools, ways to build these tools and how to deliver value from tools you can construct with little or no cost.
In this webinar, Bob will discuss tools focused on:
Formalizing accountability for governing data definition, production and use
Recording critical data governance metadata
Applying governance to existing and/or new processes
Providing necessary awareness and communications
Building and improving data understanding
Strategic imperative the enterprise data modelDATAVERSITY
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, IDERA’s 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 Role of Metadata in a Data Governance ProgramDATAVERSITY
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.
Data Governance and Data Science to Improve Data QualityDATAVERSITY
Data Science uses systematic methods, algorithms, and systems to extract knowledge and insights from structured and unstructured data. Data Science requires high-quality data that is trusted by the organization and data scientists. Many organizations focus their Data Governance programs on improving Data Quality results. These three concepts (governance, science, and quality) seem to be made for each other.
In this RWDG webinar, Bob Seiner and his special guest will discuss how the people focusing on Data Governance and Data Science must work together to improve the level of confidence the organization has in its most critical data assets. Heavy investments are being made in Data Science but not so much for Data Governance. Bob will talk about how Data Governance and Data Science must work together to improve Data Quality.
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 organization’s most important metadata.
Seiner dataversity-rwdg2017-05-operating modelofdatagovernanceroles-20170518f...DATAVERSITY
Roles and responsibilities are the foundation of a successful Data Governance program. An operating model of roles focuses on all levels of the organization including the executive, strategic, tactical and operational responsibilities. A complete model also includes roles that support the program.
In this month’s RWDG webinar, Bob Seiner will present a proven Operating Model of Data Governance Roles & Responsibilities that can be applied to the existing culture of any organization. This webinar may be the most important webinar of the year because of its impact on the rest of your data governance program.
In this webinar Bob will share information about:
The Operating Model as a pyramid diagram
Three different approaches to stewardship
Five distinct levels of responsibilities
Who is expected to participate at each level?
What will be “the ask” of these people?
RWDG Slides: What is a Data Steward to do?DATAVERSITY
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 month’s 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
Data Governance and Metadata ManagementDATAVERSITY
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. Metadata’s use has expanded beyond “data about data” 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, “You can’t have one without the other.”
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 program’s 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
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
Real-World Data Governance: Metadata to Empower Data Stewards - Introducing t...DATAVERSITY
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 – 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
This document provides an agenda and speaker bios for the "DAMA Turkey Chapter" event titled "Data Management: Where to Start?". The event will include presentations from the DAMA International President, the Teradata CTO, an ING Bank Senior Manager, a communication consultant, and a BI evangelist on topics related to data management best practices, effective communication for data managers, and practical data governance. It will take place on March 26, 2012 in Istanbul, Turkey.
Analyze This! Best Practices For Big And Fast DataEMC
During this recorded webcast, you will hear from Judith Hurwitz, noted analyst and author of Hybrid Cloud for Dummies and Bill Schmarzo, EMC Consulting’s CTO for EIMA. You will learn What is big fast data and how your organization will benefit from this transformation in data management.
This document provides an overview of portal governance and outlines an approach to establishing a portal governance framework. It defines portal governance as establishing the appropriate structures, roles, and processes to support efficient decision-making for managing a portal infrastructure and publishing new assets. It emphasizes that governance is important to coordinate the various stakeholder groups involved in a portal and prevent uncoordinated "organic" development. The document then outlines the initial steps to start a governance process, including defining what needs to be governed, how it will be governed, establishing governance teams and their roles and responsibilities, and growing and enforcing the governance over time.
Everybody is a Data Steward – Get Over It!DATAVERSITY
When Data Stewardship is based on people’s 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 month’s 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 people’s knowledge of the data that adds value for their business.
In this webinar, Bob will discuss:
Why the “Everybody is a Data Steward” 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: Knowledge Graphs vs. Property GraphsDATAVERSITY
We are in the era of graphs. Graphs are hot. Why? Flexibility is one strong driver: Heterogeneous data, integrating new data sources, and analytics all require flexibility. Graphs deliver it in spades.
Over the last few years, a number of new graph databases came to market. As we start the next decade, dare we say “the semantic twenties,” we also see vendors that never before mentioned graphs starting to position their products and solutions as graphs or graph-based.
Graph databases are one thing, but “Knowledge Graphs” are an even hotter topic. We are often asked to explain Knowledge Graphs.
Today, there are two main graph data models:
• Property Graphs (also known as Labeled Property Graphs)
• RDF Graphs (Resource Description Framework) aka Knowledge Graphs
Other graph data models are possible as well, but over 90 percent of the implementations use one of these two models. In this webinar, we will cover the following:
I. A brief overview of each of the two main graph models noted above
II. Differences in Terminology and Capabilities of these models
III. Strengths and Limitations of each approach
IV. Why Knowledge Graphs provide a strong foundation for Enterprise Data Governance and Metadata Management
Seiner dataversity - rwdg 2017-09 - how to select the appropriate data gove...DATAVERSITY
Organizations purchase Data Governance Tools to formalize responsibility and automate and assist the processes of governing data and metadata. There are many different types of tools on the market that assist in program implementation and there are several criteria and requirements that organization’s use to review and assess available tools.
In this installment of the RWDG webinar series, Bob Seiner will talk about the types of tools available on the market and requirements that can be used to assist in the selection of the most appropriate tool for your organization. Learn about the latest types of data governance tools and how to select the right one in this RWDG webinar.
Data Governance and the Internet of ThingsDATAVERSITY
Several years back there were already more devices connected to the internet than people. It is estimated that more than 20 billion devices will be connected by 2020 and that number will never fall. Connecting to the internet implies the transfer of data. The numbers of devices and what they transfer imply a lot of data. Who is governing all of this data?
Join Bob Seiner for this month’s installment of Real-World Data Governance to expand your appreciation of the data issues that pertain to the Internet of Things (IoT). You may be surprised how much of what you already know about data governance applies to governing this new definition, production and use of data.
In this webinar Bob will talk about:
•Clear Description of IoT Focused on the data
•Addressing Data Management Concerns
•Applications of IoT Data
•Dimensions of IoT Data Processes and Quality
•Risk Associated with Interoperability
This document provides a checklist report on modernizing data warehouse infrastructure. It discusses six key points regarding modernization: 1) Diversifying the portfolio of data platforms to satisfy modern data requirements, 2) Modernizing with cloud and hybrid strategies, 3) Modernizing hardware for greater speed, scale and lower costs, 4) Coordinating modernization with business and analytics modernization, 5) Adjusting data management practices to fit modern warehousing, and 6) Leveraging multi-vendor partnerships for a unified, high-performance infrastructure. The report emphasizes that modern warehouses require multiple data platform types to meet diverse needs, and that infrastructure modernization is driven by business demands for advanced analytics and self-service data practices.
Slides: Powering a Sustainable Data Governance Program – Learnings & Best Pra...DATAVERSITY
This document summarizes a presentation about E.ON Energy's data governance program. E.ON implemented a metadata management platform and data governance practices to address issues like limited data access, lack of a data catalog, and inefficient data usage. Initial results included defining data domains, connecting systems, training users, and standardizing reporting. The program aims to accelerate value from data, ensure compliance, demand trusted insights, and foster collaboration across the organization. Senior leaders must engage to support such initiatives, and building a data-driven culture is key to success.
Real-World Data Governance: Comparing World Class Solutions in Data Governanc...DATAVERSITY
This document outlines the agenda for a webinar on comparing world class data governance solutions. The webinar will feature a panel of practitioners discussing their approaches to data stewardship, metadata, and master data governance. The panelists include professionals from PNC Bank, the Church of Latter Day Saints, and the Data Governance Institute. The webinar will be moderated by Robert Seiner and cover identifying data stewards, handling metadata, governing master data, and taking questions from the audience.
RWDG Slides: Data Governance versus Information GovernanceDATAVERSITY
If Data Governance is the execution and enforcement of authority over the management of data and data-related assets, what is Information Governance? How are they the same and how do they differ? This is a question pondered by the greatest minds in Data Management. And there is no correct answer.
Join Bob Seiner for this month’s RWDG webinar where he will compare Data and Information Governance and share situations when it is makes sense to call it one over the other. Most organizations name their program after they select exactly what will be governed and how that governed “stuff” will be used. What are you governing?
In this webinar, Bob will discuss:
- Describing what it means to “Govern” something
- How to define Governance in both contexts
- Differences between Data and Information Governance
- How to select what to call your program
- Why what you call your program matters … or does it?
Enterprise Architecture vs. Data ArchitectureDATAVERSITY
Enterprise Architecture (EA) provides a visual blueprint of the organization, and shows key interrelationships between data, process, applications, and more. By abstracting these assets in a graphical view, it’s possible to see key interrelationships, particularly as they relate to data and its business impact across the organization. Join us for a discussion on how data architecture is a key component of an overall enterprise architecture for enhanced business value and success.
Real-World Data Governance: Build Your Own Data Governance ToolsDATAVERSITY
There are many tools available to assist your organization to govern your data better. The value from these tools is proven and organizations come to rely on using these tools to deliver high quality and protected data. Some of these tools are available for purchase however many can be developed and provided internally.
This RWDG webinar with Bob Seiner will address the design, development and deployment of several key instruments of data governance success. Bob will describe the purpose of these tools, ways to build these tools and how to deliver value from tools you can construct with little or no cost.
In this webinar, Bob will discuss tools focused on:
Formalizing accountability for governing data definition, production and use
Recording critical data governance metadata
Applying governance to existing and/or new processes
Providing necessary awareness and communications
Building and improving data understanding
Strategic imperative the enterprise data modelDATAVERSITY
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, IDERA’s 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 Role of Metadata in a Data Governance ProgramDATAVERSITY
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.
Data Governance and Data Science to Improve Data QualityDATAVERSITY
Data Science uses systematic methods, algorithms, and systems to extract knowledge and insights from structured and unstructured data. Data Science requires high-quality data that is trusted by the organization and data scientists. Many organizations focus their Data Governance programs on improving Data Quality results. These three concepts (governance, science, and quality) seem to be made for each other.
In this RWDG webinar, Bob Seiner and his special guest will discuss how the people focusing on Data Governance and Data Science must work together to improve the level of confidence the organization has in its most critical data assets. Heavy investments are being made in Data Science but not so much for Data Governance. Bob will talk about how Data Governance and Data Science must work together to improve Data Quality.
Data Governance vs. Information GovernanceDATAVERSITY
What is the difference between Data Governance and information governance? Organizations either use these terms interchangeably — 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 — 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:
• Similarities and differences between data and information
• Definitions of data and information governance
• Examples of how organizations have selected their label
• Brief case studies of governance named both ways
• Considerations for naming your program
Data Governance to Build Data IntelligenceDATAVERSITY
Is data intelligence a real thing? How is it related to business intelligence? Isn’t the goal of every data-focused investment to become more intelligent in how we define, produce, and use data? In this webinar these questions will be answered.
Join Bob Seiner and his special guest, Dave Kellogg, for a lively discussion on using Data Governance to build data intelligence. In this webinar, they will discuss the use of the term data intelligence and determine where it fits in the Data Management industry.
In this webinar Bob and Dave will discuss:
- A definition of Data Intelligence
- The relationship between Data Governance and Data Intelligence
- Who owns data intelligence
- How data intelligence relates to other data disciplines
- Building data intelligence through Data Governance
RWDG Webinar: Using Data Governance to Improve Data UnderstandingDATAVERSITY
For many data-focused initiatives to be considered successful, they require improved documented understanding of the organization’s data. Improvements in data understanding require accountability for the actions of putting clear definition behind your organization’s most valuable data. It makes sense that this process and associated metadata are governed.
In this month’s 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 organization’s 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 Slides: Applying Governance to Business ProcessesDATAVERSITY
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.
Driving Data Intelligence in the Supply Chain Through the Data Catalog at TJXDATAVERSITY
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 people’s “day jobs” 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
RWDG Slides: Building Data Governance Through Data StewardshipDATAVERSITY
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:
• The definition of data stewardship that MUST be adopted
• The critical role stewardship plays in governing data
• What it means to formalize accountability
• Why everybody in the organization is a data steward
• How to build Data Governance through stewardship
RWDG Slides: Build an Effective Data Governance FrameworkDATAVERSITY
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 month’s 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
Activate Data Governance Using the Data CatalogDATAVERSITY
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.
RWDG Webinar: Metadata to Support Data GovernanceDATAVERSITY
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.
Convincing Stakeholders Data Governance Is EssentialDATAVERSITY
Organizations are investing heavily in becoming data-centric. Data Governance practitioners must begin to deploy effective Data Governance techniques to support these investments. One of these techniques is to tackle the problem of convincing stakeholders that Data Governance is necessary. This webinar will help you address that challenge.
Join Bob Seiner for this RWDG webinar, where he will provide three questions that must be answered thoroughly and honestly from a business and technical perspective. The answers to these questions will provide practitioners with the artillery needed to break down barriers preventing the organization from being convinced that the time is right to formalize Data Governance.
This webinar will focus on:
- Identifying the stakeholders that must be convinced
- The three questions that must be asked of the stakeholders
- What answers you should expect to receive
- The answers that may surprise you
- Using the answers to convince stakeholders that Data Governance is necessary
RWDG Slides: The Stewardship Approach to Data GovernanceDATAVERSITY
This document discusses the stewardship approach to data governance. It describes how everybody who defines, produces, or uses data is a data steward. Rather than assigning data steward roles, the stewardship approach recognizes the existing responsibilities that people have. This reduces the invasiveness of data governance initiatives. The document provides guidance on engaging different types of data stewards based on their relationships to data and leveraging their existing responsibilities. It also addresses how the large number of stewards impacts the complexity of data governance programs and how best to deal with accountability.
RWDG Slides: Operationalize Data Governance for Business OutcomesDATAVERSITY
Data Governance adds value to the organization when it becomes operationalized and focused on providing improved business outcomes. People in the organization acknowledge Data Governance success when they see results based on how the formalized program operates.
Join Bob Seiner for this month’s webinar, where he will focus on how to operationalize Data Governance based on your program’s purpose and demonstrate value through the communications of business outcomes. New ways to operationalize Data Governance and engage data stewards will be highlighted.
Bob will discuss :
• What it means to operationalize Data Governance
• How to link Data Governance to business outcomes – both good and bad
• Program operations designed to provide business outcomes
• Using the program purpose to demonstrate value
• Ways to engage your stewards through their job function
RWDG Webinar: Big Data & BI Analytics Require Data GovernanceDATAVERSITY
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 – 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
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 Slides: Metadata Governance for Catalogs, Glossaries, Dictionaries, and ...DATAVERSITY
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 month’s 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
To take a “ready, aim, fire” 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
Who Should Own Data Governance – IT or Business?DATAVERSITY
The question is asked all the time: “What part of the organization should own your Data Governance program?” The typical answers are “the business” and “IT (information technology).” Another answer to that question is “Yes.” 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 “the business” 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
Real-World Data Governance Webinar: Data Governance Framework ComponentsDATAVERSITY
There are several basic components that go into delivering a successful and sustainable data governance program. Many of these framework items can be developed using tools you already own and without going to great expense. Organizations swear by the items that will be discussed in this webinar.
Join Bob Seiner for this month’s installment of the Real-World Data Governance series to learn about how to build and deliver immediate and future value from your Data Governance program through the delivery of items that will formalize accountability for the management of data and information assets.
Bob will discuss these core components:
Gaining Leadership’s backing and understanding
Best Practice Analysis leading to Recommended Actions
Operating Model of Roles & Responsibilities
Communications Plan to improve awareness
Action Plan / Roadmap to success
Similar to RWDG Slides: Data and Metadata Will Not Govern Themselves (20)
Architecture, Products, and Total Cost of Ownership of the Leading Machine Le...DATAVERSITY
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 enterprise’s most pressing data and analytic challenges in a streamlined fashion.
In this research-based session, I’ll 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
Do you ever wonder how data-driven organizations fuel analytics, improve customer experience, and accelerate business productivity? They are successful by governing and mastering data effectively so they can get trusted data to those who need it faster. Efficient data discovery, mastering and democratization is critical for swiftly linking accurate data with business consumers. 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.
Join data mastering and data governance experts from Informatica—plus a real-world organization empowering trusted data for analytics—for a lively panel discussion. You’ll hear more about how a single cloud-native approach can help global businesses in any economy create more value—faster, more reliably, and with more confidence—by 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.
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 “literacy” such as business acumen?
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 – Practical Steps for Aligning with Business GoalsDATAVERSITY
Developing a Data Strategy for your organization can seem like a daunting task – but it’s worth the effort. Getting your Data Strategy right can provide significant value, as data drives many of the key initiatives in today’s marketplace – 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 – 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 – What is the Question?DATAVERSITY
Organizations with governed metadata made available through their data catalog can answer questions their people have about the organization’s 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 stewards’ 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 – What Is the Question?DATAVERSITY
Organizations with governed metadata made available through their data catalog can answer questions their people have about the organization’s 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 stewards’ 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 people’s 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 world’s consciousness. For many organizations in various industries, though, comprehension of this development begins and ends with buzzwords: “Big Data,” “NoSQL,” “Data Scientist,” 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 organization’s 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
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 doesn’t 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 – having a data-fluent workforce – is attractive, we wonder how (and if) we can get there.
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 – Privacy, Security & Governance Race from Reactivity to Re...DATAVERSITY
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 – not just react – 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 – 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
You’ll 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 – What’s the Next Big Thing?DATAVERSITY
With technological innovation and change occurring at an ever-increasing rate, it’s hard to keep track of what’s 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.
Data Governance Trends - A Look Backwards and ForwardsDATAVERSITY
As DATAVERSITY’s 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.
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.
In this webinar, Bob will focus on:
- Data Governance’s past, present, and future
- How trials and tribulations evolve to success
- Leveraging lessons learned to improve productivity
- The great Data Governance tool explosion
- The future of Data Governance
Data Governance Trends and Best Practices To Implement TodayDATAVERSITY
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 you’re in, you’re 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 “Can you help me with our data strategy?” 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: “Can you help me apply data strategically?” 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 –particularly given the widespread acceptance of Mike Tyson’s truism: “Everybody has a plan until they get punched in the face.” 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. Learn how to improve the following:
- Your organization’s 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
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 – Applying DevOps to Competitive AdvantageDATAVERSITY
MLOps is a practice for collaboration between Data Science and operations to manage the production machine learning (ML) lifecycles. As an amalgamation of “machine learning” and “operations,” 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.
Keeping the Pulse of Your Data – Why You Need Data Observability to Improve D...DATAVERSITY
This document discusses the importance of data observability for improving data quality. It begins with an introduction to data observability and how it works by continuously monitoring data to detect anomalies and issues. This is unlike traditional reactive approaches. Examples are then provided of how unexpected data values or volumes could negatively impact downstream processes but be resolved quicker with data observability alerts. The document emphasizes that data observability allows issues to be identified and addressed before they become costly problems. It promotes data observability as a way to proactively improve data integrity and ensure accurate, consistent data for confident decision making.
Did you know that drowning is a leading cause of unintentional death among young children? According to recent data, children aged 1-4 years are at the highest risk. Let's raise awareness and take steps to prevent these tragic incidents. Supervision, barriers around pools, and learning CPR can make a difference. Stay safe this summer!
06-18-2024-Princeton Meetup-Introduction to MilvusTimothy Spann
06-18-2024-Princeton Meetup-Introduction to Milvus
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Expand LLMs' knowledge by incorporating external data sources into LLMs and your AI applications.
We are pleased to share with you the latest VCOSA statistical report on the cotton and yarn industry for the month of March 2024.
Starting from January 2024, the full weekly and monthly reports will only be available for free to VCOSA members. To access the complete weekly report with figures, charts, and detailed analysis of the cotton fiber market in the past week, interested parties are kindly requested to contact VCOSA to subscribe to the newsletter.
Essential Skills for Family Assessment - Marital and Family Therapy and Couns...PsychoTech Services
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!
Do People Really Know Their Fertility Intentions? Correspondence between Sel...Xiao Xu
Fertility intention data from surveys often serve as a crucial component in modeling fertility behaviors. Yet, the persistent gap between stated intentions and actual fertility decisions, coupled with the prevalence of uncertain responses, has cast doubt on the overall utility of intentions and sparked controversies about their nature. In this study, we use survey data from a representative sample of Dutch women. With the help of open-ended questions (OEQs) on fertility and Natural Language Processing (NLP) methods, we are able to conduct an in-depth analysis of fertility narratives. Specifically, we annotate the (expert) perceived fertility intentions of respondents and compare them to their self-reported intentions from the survey. Through this analysis, we aim to reveal the disparities between self-reported intentions and the narratives. Furthermore, by applying neural topic modeling methods, we could uncover which topics and characteristics are more prevalent among respondents who exhibit a significant discrepancy between their stated intentions and their probable future behavior, as reflected in their narratives.
Discovering Digital Process Twins for What-if Analysis: a Process Mining Appr...Marlon Dumas
This webinar discusses the limitations of traditional approaches for business process simulation based on had-crafted model with restrictive assumptions. It shows how process mining techniques can be assembled together to discover high-fidelity digital twins of end-to-end processes from event data.
3. Data Intelligence Solves the Data Dilemma
Harvest Data
2
Organize Data Curate Data Supervise Data Socialize Data
Data
Development
Data
Operations
Data
Governance
Data
Consumption
6. Key Automation Points for Data Intelligence
Enable Sustainable Data Governance
5
Auto Document
Data Sources
Data Models
Data Movement Processes
Data Consumption Points
Auto Configure & Classify
Technical Asset Associations
Business Asset Associations
Business-Technical
Associations
Sensitivity Classifications
Auto Render & Navigate
End-to-End Lineage
Impact Analysis
Visual Mind Maps
Dashboards
Auto Generate
Data Pipelines
Data Workloads
Data Movement Code
Platform Orchestration
Reduce: Time, Cost, Latency, Risk
Increase: Agility, Accuracy, Portability, Scalability