Big Data is an increasingly powerful enterprise asset and this talk will explore the relationship between big data and cyber security, how we preserve privacy whilst exploiting the advantages of data collection and processing. Big Data technologies provide both governments and corporations powerful tools to offer more efficient and personalized services. The rapid adoption of these technologies has of course created tremendous social benefits. Unfortunately unwanted side effects are the potential rich pickings available to those with malicious intentions. Increasingly, the sophisticated cyber attacker is able to exploit the rich array public data to build detailed profiles on their adversaries to support their malicious intentions
Preparing for the Cybersecurity RenaissanceCloudera, Inc.
We are in the midst of a fundamental shift in the way in which organizations protect themselves from the modern adversary.
Traditional rules based cybersecurity applications of the past are not able to protect organizations in the new mobile, social, and hyper-connected world they now operate within. However, the convergence of big data technology, analytic advancements, and a variety of other factors have sparked a cybersecurity renaissance that will forever change the way in which organizations protect themselves.
Join Rocky DeStefano, Cloudera's Cybersecurity subject matter expert, as he explores how modern organizations are protecting themselves from more frequent, sophisticated attacks.
During this webinar you will learn about:
The current challenges cybersecurity professionals are facing today
How big data technologies are extending the capabilities of cybersecurity applications
Cloudera customers that are future proofing their cybersecurity posture with Cloudera’s next generation data and analytics management system
Cloudera's big data platform can help organizations comply with the EU's General Data Protection Regulation (GDPR) in three key ways:
1. It provides a single system to securely store, govern, and manage all analytic workloads and personal data across on-premises, cloud, structured, and unstructured data sources.
2. Its shared services like data catalog, security, governance, and lifecycle management can be applied uniformly across the platform to meet GDPR principles like data minimization, storage limitation, and accuracy.
3. Specific capabilities like its GDPR data hub, consent management, and ability to delete individual data records upon request help automate key GDPR requirements at scale,
Seeking Cybersecurity--Strategies to Protect the DataCloudera, Inc.
Agency professionals are responsible for protecting the data they collect, store, analyze, and share. While Hadoop has been especially popular for data analytics given its ability to handle volume, velocity, and variety of data, this flexibility and scale can present challenges for securing and governing the data. Plan to attend this session to understand the Hadoop Security Maturity Model—from the fundamentals to the latest developments--and how to ensure your data analytics cluster complies with the latest INFOSEC standards and audit requirements. Bring your experience and your questions to this informative and interactive cybersecurity session.
This document discusses security challenges related to big data and Hadoop. It notes that as data grows exponentially, the complexity of managing, securing, and enforcing privacy restrictions on data sets increases. Organizations now need to control access to data scientists based on authorization levels and what data they are allowed to see. Mismanagement of data sets can be costly, as shown by incidents at AOL, Netflix, and a Massachusetts hospital that led to lawsuits and fines. The document then provides a brief history of Hadoop security, noting that it was originally developed without security in mind. It outlines the current Kerberos-centric security model and talks about some vendor solutions emerging to enhance Hadoop security. Finally, it provides guidance on developing security and privacy
Project Rhino: Enhancing Data Protection for HadoopCloudera, Inc.
Learn the history of Project Rhino and its importance, the progress that’s been made so far (including a deep dive into the new security features announced with CDH 5.3), and what’s next for Hadoop security.
Delivering User Behavior Analytics at Apache Hadoop Scale : A new perspective...Cloudera, Inc.
Learn how to:
* Detect threats automatically and accurately
* Reduce threat response times from 7 days to 4 hour
* Ingest and process 100+TB per day for automated machine learning and behavior-based detection
Spark and Deep Learning Frameworks at Scale 7.19.18Cloudera, Inc.
We'll outline approaches for preprocessing, training, inference, and deployment across datasets (time series, audio, video, text, etc.) that leverage Spark, along with its extended ecosystem of libraries and deep learning frameworks using Cloudera's Data Science Workbench.
Discover the origins of big data, discuss existing and new projects, share common use cases for those projects, and explain how you can modernize your architecture using data analytics, data operations, data engineering and data science.
Big Data Fundamentals is your prerequisite to building a modern platform for machine learning and analytics optimized for the cloud.
We’ll close out with a live Q&A with some of our technical experts as well.
Stretch your brain with a packed agenda:
Open source software
Data storage
Data ingestion
Data analytics
Data engineering
IoT and life after Lambda architectures
Data science
Cybersecurity
Cluster management
Big data in the cloud
Success stories
Preparing for the Cybersecurity RenaissanceCloudera, Inc.
We are in the midst of a fundamental shift in the way in which organizations protect themselves from the modern adversary.
Traditional rules based cybersecurity applications of the past are not able to protect organizations in the new mobile, social, and hyper-connected world they now operate within. However, the convergence of big data technology, analytic advancements, and a variety of other factors have sparked a cybersecurity renaissance that will forever change the way in which organizations protect themselves.
Join Rocky DeStefano, Cloudera's Cybersecurity subject matter expert, as he explores how modern organizations are protecting themselves from more frequent, sophisticated attacks.
During this webinar you will learn about:
The current challenges cybersecurity professionals are facing today
How big data technologies are extending the capabilities of cybersecurity applications
Cloudera customers that are future proofing their cybersecurity posture with Cloudera’s next generation data and analytics management system
Cloudera's big data platform can help organizations comply with the EU's General Data Protection Regulation (GDPR) in three key ways:
1. It provides a single system to securely store, govern, and manage all analytic workloads and personal data across on-premises, cloud, structured, and unstructured data sources.
2. Its shared services like data catalog, security, governance, and lifecycle management can be applied uniformly across the platform to meet GDPR principles like data minimization, storage limitation, and accuracy.
3. Specific capabilities like its GDPR data hub, consent management, and ability to delete individual data records upon request help automate key GDPR requirements at scale,
Seeking Cybersecurity--Strategies to Protect the DataCloudera, Inc.
Agency professionals are responsible for protecting the data they collect, store, analyze, and share. While Hadoop has been especially popular for data analytics given its ability to handle volume, velocity, and variety of data, this flexibility and scale can present challenges for securing and governing the data. Plan to attend this session to understand the Hadoop Security Maturity Model—from the fundamentals to the latest developments--and how to ensure your data analytics cluster complies with the latest INFOSEC standards and audit requirements. Bring your experience and your questions to this informative and interactive cybersecurity session.
This document discusses security challenges related to big data and Hadoop. It notes that as data grows exponentially, the complexity of managing, securing, and enforcing privacy restrictions on data sets increases. Organizations now need to control access to data scientists based on authorization levels and what data they are allowed to see. Mismanagement of data sets can be costly, as shown by incidents at AOL, Netflix, and a Massachusetts hospital that led to lawsuits and fines. The document then provides a brief history of Hadoop security, noting that it was originally developed without security in mind. It outlines the current Kerberos-centric security model and talks about some vendor solutions emerging to enhance Hadoop security. Finally, it provides guidance on developing security and privacy
Project Rhino: Enhancing Data Protection for HadoopCloudera, Inc.
Learn the history of Project Rhino and its importance, the progress that’s been made so far (including a deep dive into the new security features announced with CDH 5.3), and what’s next for Hadoop security.
Delivering User Behavior Analytics at Apache Hadoop Scale : A new perspective...Cloudera, Inc.
Learn how to:
* Detect threats automatically and accurately
* Reduce threat response times from 7 days to 4 hour
* Ingest and process 100+TB per day for automated machine learning and behavior-based detection
Spark and Deep Learning Frameworks at Scale 7.19.18Cloudera, Inc.
We'll outline approaches for preprocessing, training, inference, and deployment across datasets (time series, audio, video, text, etc.) that leverage Spark, along with its extended ecosystem of libraries and deep learning frameworks using Cloudera's Data Science Workbench.
Discover the origins of big data, discuss existing and new projects, share common use cases for those projects, and explain how you can modernize your architecture using data analytics, data operations, data engineering and data science.
Big Data Fundamentals is your prerequisite to building a modern platform for machine learning and analytics optimized for the cloud.
We’ll close out with a live Q&A with some of our technical experts as well.
Stretch your brain with a packed agenda:
Open source software
Data storage
Data ingestion
Data analytics
Data engineering
IoT and life after Lambda architectures
Data science
Cybersecurity
Cluster management
Big data in the cloud
Success stories
Comprehensive Security for the Enterprise IV: Visibility Through a Single End...Cloudera, Inc.
To provide visibility and transparency into your data and usage, Cloudera Enterprise has Navigator, the only native end-to-end governance solution for Apache Hadoop. In this webinar we discuss why Navigator is a key part of comprehensive security and discuss its key features including: auditing, access control, data discovery and exploration, lineage, and lifecycle management. Live demo also included.
The 5 Biggest Data Myths in Telco: ExposedCloudera, Inc.
The document discusses common myths in the telecommunications industry regarding big data and analytics. It addresses five myths: 1) that data is too diverse to analyze, 2) that open source means open security, 3) that big data platforms do not provide adequate return on investment, 4) that big data tools are too difficult for teams to learn, and 5) that legacy systems cannot handle additional data solutions. For each myth, it provides facts and examples to demonstrate why the myths are unfounded and how organizations can leverage big data to drive insights.
How to Build Continuous Ingestion for the Internet of ThingsCloudera, Inc.
The Internet of Things is moving into the mainstream and this new world of data-driven products is transforming a vast number of industry sectors and technologies.
However, IoT creates a new challenge: how to build and operationalize continual data ingestion from such a wide and ever-changing array of endpoints so that the data arrives consumption-ready and can drive analysis and action within the business.
In this webinar, Sean Anderson from Cloudera and Kirit Busu, Director of Product Management at StreamSets, will discuss Hadoop's ecosystem and IoT capabilities and provide advice about common patterns and best practices. Using specific examples, they will demonstrate how to build and run end-to-end IOT data flows using StreamSets and Cloudera infrastructure.
Risk Management for Data: Secured and GovernedCloudera, Inc.
Cloudera Tech Day Presentation by Eddie Garcia, Chief Security Architect, Cloudera. Protecting enterprise data is an increasingly complex challenge given the diversity and sophistication of threat actors and their cyber-tactics. In this session, participants will hear a comprehensive introduction to Hadoop Security, including the “three A’s” for secure operating environments: Authentication, Authorization, and Audit. In addition, the presenter will cover strategies to orchestrate data security, encryption, and compliance, and will explain the Cloudera Security Maturity Model for Hadoop. Attendees will leave with a greater understanding of how effective INFOSEC relies on an enterprise big data governance and risk management approach.
This document discusses using Hadoop to fight cyber fraud by analyzing big data. It explains that big data technologies provide powerful tools for services but also enable malicious cyber attacks by sophisticated attackers. Hadoop allows analyzing large datasets to detect fraud and security threats through techniques like machine learning, anomaly detection, and predicting real-time and historical patterns. The document advocates asking bigger questions to innovate solutions and gain operational and business advantages from big data analytics.
Protecting health and life science organizations from breaches and ransomwareCloudera, Inc.
3 Things to Learn About:
* 1. Ransomware is a particular problem and currently the highest priority for healthcare organizations. Machine learning can use the structure of a malicious email to detect an attack even before the email is opened.
* 2. Big data architectures provide the machine-learning models with the volume and variety of data required to achieve complete visibility across the spectrum of IT activity—from packets to logs to alerts.
* 3. Intel and industry partners are currently running one-hour, complimentary, confidential benchmark engagements for HLS organizations that want to see how their security compares with the industry .
Cloudera training secure your cloudera cluster 7.10.18Cloudera, Inc.
Exclusively through Cloudera OnDemand, Cloudera Security Training introduces you to the tools and techniques that Cloudera's solution architects use to protect the clusters our customers rely on for critical machine learning and analytics workloads. This webinar will give you a sneak peek at our new on-demand security course and show you the immense scope of Cloudera training. From authentication and authorization to encryption, auditing, and everything in between, this course gives you the skills you need to properly secure your Cloudera cluster.
Relying on Data for Strategic Decision-Making--Financial Services ExperienceCloudera, Inc.
This document discusses how financial services companies can leverage big data and machine learning to drive strategic decision making through improved customer insights and risk management. It outlines key data challenges around data silos, volume, and costs. Example use cases are provided for building customer 360 profiles and improving fraud detection. The presentation argues that an enterprise data hub on Cloudera can help integrate diverse data sources, power real-time analytics at scale, and enable new business opportunities in areas like customer experience and risk compliance.
To disrupt and innovate, you need access to data. All of your data. The challenge for many organisations is that the data they need is locked away in a variety of silos. And there's perhaps no bigger silo than one of the most a widely deployed business application: SAP. Bringing together all your data for analytics and machine learning unlocks new insights and business value. Together, Cloudera and Datavard hold the key to breaking SAP data out of its silo, providing access to unlimited and untapped opportunities that currently lay hidden.
Cloudera training: secure your Cloudera clusterCloudera, Inc.
The first and possibly most important task you perform when you deploy your Cloudera cluster is securing it. Get it wrong and you may inadvertently and unknowingly have introduced a risk to the business. Getting it right eventually leaves you looking back at wasted efforts and false starts. So how do you get it right first time?
Hortonworks Hybrid Cloud - Putting you back in control of your dataScott Clinton
The document discusses Hortonworks' solutions for managing data across hybrid cloud environments. It proposes getting all data under management, combating growing cloud data silos, and consistently securing and governing data across locations. Hortonworks offers the Hortonworks Data Platform, Hortonworks Dataflow, and Hortonworks DataPlane to provide a modern hybrid data architecture with cloud-native capabilities, security and governance, and the ability to extend to edge locations. The document also highlights Hortonworks' professional services and open source community initiatives around hybrid cloud data.
Delivering improved patient outcomes through advanced analytics 6.26.18Cloudera, Inc.
Rush University Medical Center, along with Cloudera and MetiStream, talk about adopting a comprehensive and interactive analytic platform for improved patient outcomes and better genomic analysis, highlighting examples in both genomics and clinical notes. John Spooner of 451 Research provides context to the discussion and shares market insights that complement the customer stories.
2016 Cybersecurity Analytics State of the UnionCloudera, Inc.
3 Things to Learn About:
-Ponemon Institute's 2016 big data cybersecurity analytics research report
-Quantifiable returns organizations are seeing with big data cybersecurity analytics
-Trends in the industry that are affecting cybersecurity strategies
Hadoop Essentials -- The What, Why and How to Meet Agency ObjectivesCloudera, Inc.
This session will provide an executive overview of the Apache Hadoop ecosystem, its basic concepts, and its real-world applications. Attendees will learn how organizations worldwide are using the latest tools and strategies to harness their enterprise information to solve business problems and the types of data analysis commonly powered by Hadoop. Learn how various projects make up the Apache Hadoop ecosystem and the role each plays to improve data storage, management, interaction, and analysis. This is a valuable opportunity to gain insights into Hadoop functionality and how it can be applied to address compelling business challenges in your agency.
Is your big data journey stalling? Take the Leap with Capgemini and ClouderaCloudera, Inc.
Transitioning to a Big Data architecture is a big step; and the complexity of moving existing analytical services onto modern platforms like Cloudera, can seem overwhelming.
Data is being generated at a feverish pace and many businesses want all of it at their disposal to solve complex strategic problems. As decision making moves to real-time, enterprises need data ready for analysis immediately. Sean Anderson and Amandeep Khurana will discuss common pipeline trends in modern streaming architectures, Hadoop components that enable streaming capabilities, and popular use cases that are enabling the world of IOT and real-time data science.
Standing Up an Effective Enterprise Data Hub -- Technology and BeyondCloudera, Inc.
Federal organizations increasingly are focused on creating environments that enable more data-driven decisions. Yet ensuring that all data is considered and is current, complete, and accurate is a tall order for most. To make data analytics meaningful to support real-world transformation, agency staff need business tools that provide user-friendly dashboards, on-demand reporting, and methods to manage efficiently the rise of voluminous and varied data sets and types commonly associated with big data. In most cases, existing systems are insufficient to support these requirements. Enter the enterprise data hub (EDH), a software architecture specifically designed to be a unified platform that can economically store unlimited data and enable diverse access to it at scale. Plan to attend this discussion to understand the key considerations to making an EDH the architectural center of your agency’s modern data strategy.
Using Hadoop to Drive Down Fraud for TelcosCloudera, Inc.
Communication Service Providers (CSPs) lose around $38 Billion to fraud every year. Check out this webinar to learn more about the Cloudera - Argyle Data real-time fraud analytics platform and how Telcos can utilize Apache Hadoop to drive down fraud.
How komatsu is driving operational efficiencies using io t and machine learni...Cloudera, Inc.
In this joint webinar, Jason Knuth, data scientist and analytics lead at Komatsu shares how they are analyzing over 17 billion data points every day from connected devices and using machine learning and analytics to improve mining operations.
The Future of Data Management - the Enterprise Data HubDataWorks Summit
The document discusses security for Hadoop systems. It outlines key requirements for Hadoop security including perimeter protection, data protection, access control and visibility. It then details Cloudera's current and planned security capabilities for authentication, authorization, auditing, encryption and key management. Examples are given of companies using Cloudera security solutions to meet compliance requirements and protect sensitive data in Hadoop.
The Future of Hadoop Security - Hadoop Summit 2014Cloudera, Inc.
Hadoop deployments are rapidly moving from pilots to production, enabling unprecedented opportunity to build big data applications that deliver faster access to more information to more users than ever before possible. Yet without the ability to address data security and compliance regulations, Hadoop will be limited to another data silo.
In this talk, Matt Brandwein and David Tishgart discuss the requirements for securing Hadoop and how Cloudera (now with Gazzang) and Intel are collaborating in the open to deliver comprehensive, transparent, compliance-ready security to unlock the potential of the Hadoop ecosystem and enable innovation without compromise.
Comprehensive Security for the Enterprise IV: Visibility Through a Single End...Cloudera, Inc.
To provide visibility and transparency into your data and usage, Cloudera Enterprise has Navigator, the only native end-to-end governance solution for Apache Hadoop. In this webinar we discuss why Navigator is a key part of comprehensive security and discuss its key features including: auditing, access control, data discovery and exploration, lineage, and lifecycle management. Live demo also included.
The 5 Biggest Data Myths in Telco: ExposedCloudera, Inc.
The document discusses common myths in the telecommunications industry regarding big data and analytics. It addresses five myths: 1) that data is too diverse to analyze, 2) that open source means open security, 3) that big data platforms do not provide adequate return on investment, 4) that big data tools are too difficult for teams to learn, and 5) that legacy systems cannot handle additional data solutions. For each myth, it provides facts and examples to demonstrate why the myths are unfounded and how organizations can leverage big data to drive insights.
How to Build Continuous Ingestion for the Internet of ThingsCloudera, Inc.
The Internet of Things is moving into the mainstream and this new world of data-driven products is transforming a vast number of industry sectors and technologies.
However, IoT creates a new challenge: how to build and operationalize continual data ingestion from such a wide and ever-changing array of endpoints so that the data arrives consumption-ready and can drive analysis and action within the business.
In this webinar, Sean Anderson from Cloudera and Kirit Busu, Director of Product Management at StreamSets, will discuss Hadoop's ecosystem and IoT capabilities and provide advice about common patterns and best practices. Using specific examples, they will demonstrate how to build and run end-to-end IOT data flows using StreamSets and Cloudera infrastructure.
Risk Management for Data: Secured and GovernedCloudera, Inc.
Cloudera Tech Day Presentation by Eddie Garcia, Chief Security Architect, Cloudera. Protecting enterprise data is an increasingly complex challenge given the diversity and sophistication of threat actors and their cyber-tactics. In this session, participants will hear a comprehensive introduction to Hadoop Security, including the “three A’s” for secure operating environments: Authentication, Authorization, and Audit. In addition, the presenter will cover strategies to orchestrate data security, encryption, and compliance, and will explain the Cloudera Security Maturity Model for Hadoop. Attendees will leave with a greater understanding of how effective INFOSEC relies on an enterprise big data governance and risk management approach.
This document discusses using Hadoop to fight cyber fraud by analyzing big data. It explains that big data technologies provide powerful tools for services but also enable malicious cyber attacks by sophisticated attackers. Hadoop allows analyzing large datasets to detect fraud and security threats through techniques like machine learning, anomaly detection, and predicting real-time and historical patterns. The document advocates asking bigger questions to innovate solutions and gain operational and business advantages from big data analytics.
Protecting health and life science organizations from breaches and ransomwareCloudera, Inc.
3 Things to Learn About:
* 1. Ransomware is a particular problem and currently the highest priority for healthcare organizations. Machine learning can use the structure of a malicious email to detect an attack even before the email is opened.
* 2. Big data architectures provide the machine-learning models with the volume and variety of data required to achieve complete visibility across the spectrum of IT activity—from packets to logs to alerts.
* 3. Intel and industry partners are currently running one-hour, complimentary, confidential benchmark engagements for HLS organizations that want to see how their security compares with the industry .
Cloudera training secure your cloudera cluster 7.10.18Cloudera, Inc.
Exclusively through Cloudera OnDemand, Cloudera Security Training introduces you to the tools and techniques that Cloudera's solution architects use to protect the clusters our customers rely on for critical machine learning and analytics workloads. This webinar will give you a sneak peek at our new on-demand security course and show you the immense scope of Cloudera training. From authentication and authorization to encryption, auditing, and everything in between, this course gives you the skills you need to properly secure your Cloudera cluster.
Relying on Data for Strategic Decision-Making--Financial Services ExperienceCloudera, Inc.
This document discusses how financial services companies can leverage big data and machine learning to drive strategic decision making through improved customer insights and risk management. It outlines key data challenges around data silos, volume, and costs. Example use cases are provided for building customer 360 profiles and improving fraud detection. The presentation argues that an enterprise data hub on Cloudera can help integrate diverse data sources, power real-time analytics at scale, and enable new business opportunities in areas like customer experience and risk compliance.
To disrupt and innovate, you need access to data. All of your data. The challenge for many organisations is that the data they need is locked away in a variety of silos. And there's perhaps no bigger silo than one of the most a widely deployed business application: SAP. Bringing together all your data for analytics and machine learning unlocks new insights and business value. Together, Cloudera and Datavard hold the key to breaking SAP data out of its silo, providing access to unlimited and untapped opportunities that currently lay hidden.
Cloudera training: secure your Cloudera clusterCloudera, Inc.
The first and possibly most important task you perform when you deploy your Cloudera cluster is securing it. Get it wrong and you may inadvertently and unknowingly have introduced a risk to the business. Getting it right eventually leaves you looking back at wasted efforts and false starts. So how do you get it right first time?
Hortonworks Hybrid Cloud - Putting you back in control of your dataScott Clinton
The document discusses Hortonworks' solutions for managing data across hybrid cloud environments. It proposes getting all data under management, combating growing cloud data silos, and consistently securing and governing data across locations. Hortonworks offers the Hortonworks Data Platform, Hortonworks Dataflow, and Hortonworks DataPlane to provide a modern hybrid data architecture with cloud-native capabilities, security and governance, and the ability to extend to edge locations. The document also highlights Hortonworks' professional services and open source community initiatives around hybrid cloud data.
Delivering improved patient outcomes through advanced analytics 6.26.18Cloudera, Inc.
Rush University Medical Center, along with Cloudera and MetiStream, talk about adopting a comprehensive and interactive analytic platform for improved patient outcomes and better genomic analysis, highlighting examples in both genomics and clinical notes. John Spooner of 451 Research provides context to the discussion and shares market insights that complement the customer stories.
2016 Cybersecurity Analytics State of the UnionCloudera, Inc.
3 Things to Learn About:
-Ponemon Institute's 2016 big data cybersecurity analytics research report
-Quantifiable returns organizations are seeing with big data cybersecurity analytics
-Trends in the industry that are affecting cybersecurity strategies
Hadoop Essentials -- The What, Why and How to Meet Agency ObjectivesCloudera, Inc.
This session will provide an executive overview of the Apache Hadoop ecosystem, its basic concepts, and its real-world applications. Attendees will learn how organizations worldwide are using the latest tools and strategies to harness their enterprise information to solve business problems and the types of data analysis commonly powered by Hadoop. Learn how various projects make up the Apache Hadoop ecosystem and the role each plays to improve data storage, management, interaction, and analysis. This is a valuable opportunity to gain insights into Hadoop functionality and how it can be applied to address compelling business challenges in your agency.
Is your big data journey stalling? Take the Leap with Capgemini and ClouderaCloudera, Inc.
Transitioning to a Big Data architecture is a big step; and the complexity of moving existing analytical services onto modern platforms like Cloudera, can seem overwhelming.
Data is being generated at a feverish pace and many businesses want all of it at their disposal to solve complex strategic problems. As decision making moves to real-time, enterprises need data ready for analysis immediately. Sean Anderson and Amandeep Khurana will discuss common pipeline trends in modern streaming architectures, Hadoop components that enable streaming capabilities, and popular use cases that are enabling the world of IOT and real-time data science.
Standing Up an Effective Enterprise Data Hub -- Technology and BeyondCloudera, Inc.
Federal organizations increasingly are focused on creating environments that enable more data-driven decisions. Yet ensuring that all data is considered and is current, complete, and accurate is a tall order for most. To make data analytics meaningful to support real-world transformation, agency staff need business tools that provide user-friendly dashboards, on-demand reporting, and methods to manage efficiently the rise of voluminous and varied data sets and types commonly associated with big data. In most cases, existing systems are insufficient to support these requirements. Enter the enterprise data hub (EDH), a software architecture specifically designed to be a unified platform that can economically store unlimited data and enable diverse access to it at scale. Plan to attend this discussion to understand the key considerations to making an EDH the architectural center of your agency’s modern data strategy.
Using Hadoop to Drive Down Fraud for TelcosCloudera, Inc.
Communication Service Providers (CSPs) lose around $38 Billion to fraud every year. Check out this webinar to learn more about the Cloudera - Argyle Data real-time fraud analytics platform and how Telcos can utilize Apache Hadoop to drive down fraud.
How komatsu is driving operational efficiencies using io t and machine learni...Cloudera, Inc.
In this joint webinar, Jason Knuth, data scientist and analytics lead at Komatsu shares how they are analyzing over 17 billion data points every day from connected devices and using machine learning and analytics to improve mining operations.
The Future of Data Management - the Enterprise Data HubDataWorks Summit
The document discusses security for Hadoop systems. It outlines key requirements for Hadoop security including perimeter protection, data protection, access control and visibility. It then details Cloudera's current and planned security capabilities for authentication, authorization, auditing, encryption and key management. Examples are given of companies using Cloudera security solutions to meet compliance requirements and protect sensitive data in Hadoop.
The Future of Hadoop Security - Hadoop Summit 2014Cloudera, Inc.
Hadoop deployments are rapidly moving from pilots to production, enabling unprecedented opportunity to build big data applications that deliver faster access to more information to more users than ever before possible. Yet without the ability to address data security and compliance regulations, Hadoop will be limited to another data silo.
In this talk, Matt Brandwein and David Tishgart discuss the requirements for securing Hadoop and how Cloudera (now with Gazzang) and Intel are collaborating in the open to deliver comprehensive, transparent, compliance-ready security to unlock the potential of the Hadoop ecosystem and enable innovation without compromise.
Comprehensive Security for the Enterprise III: Protecting Data at Rest and In...Cloudera, Inc.
This webinar discusses how you can use Navigator capabilities such as Encrypt and Key Trustee to secure data and enable compliance. Additionally, we will discuss our joint work with Intel on Project Rhino (an initiative to improve data security in Hadoop). We also hear from a security architect at a financial services company that is using encryption and key management to meet financial regulatory requirements.
This document provides an overview of Apache Hadoop security, both historically and what is currently available and planned for the future. It discusses how Hadoop security is different due to benefits like combining previously siloed data and tools. The four areas of enterprise security - perimeter, access, visibility, and data protection - are reviewed. Specific security capabilities like Kerberos authentication, Apache Sentry role-based access control, Cloudera Navigator auditing and encryption, and HDFS encryption are summarized. Planned future enhancements are also mentioned like attribute-based access controls and improved encryption capabilities.
Comprehensive Security for the Enterprise II: Guarding the Perimeter and Cont...Cloudera, Inc.
One of the benefits of Hadoop is that it easily allows for multiple entry points both for data flow and user access. Here we discuss how Cloudera allows you to preserve the agility of having multiple entry points while also providing strong, easy to manage authentication. Additionally, we discuss how Cloudera provides unified authorization to easily control access for multiple data processing engines.
The fundamentals and best practices of securing your Hadoop cluster are top of mind today. In this session, we will examine and explain the components, tools, and frameworks used in Hadoop for authentication, authorization, audit, and encryption of data and processes. See how the latest innovations can let you securely connect more data to more users within your organization.
IoT is reshaping the manufacturing and industrial processes, effectively changing the paradigm from one of repair and replace to more of predict and prevent. Using data streaming from connected equipment and machinery, organizations can now monitor the health of their assets and effectively predict when and how an asset might fail. However, without the right data management strategy and tools, investments in IoT can yield limited results. Join Cloudera and Tata Consultancy Services (TCS) for a joint webinar to learn more about how organizations are using advanced analytics and machine learning to drive IoT enabled predictive maintenance.
Big Data Everywhere Chicago: The Big Data Imperative -- Discovering & Protect...BigDataEverywhere
Today, no industry is immune from a potential data breach and the havoc it can create. According to a 2013 Global Data Breach study by the Ponemon Institute, the average cost of data loss exceeds $5.4 million per breach, and the average per person cost of lost data is approaching $200 per record in the US. Protecting sensitive data in Hadoop is now the imperative for IT and business. With the emergence of Hadoop as a business-critical data platform, Hadoop offers organizations opportunities to improve performance, better understand customers and develop a competitive advantage. But reaching these desirable analytic outcomes depends on the ability to use data without exposing the organization to unnecessary risk. This presentation will cover best practices for a data-centric security, compliance and data governance approach, with a particular focus on two customer use cases within the financial services and insurance industries. You'll learn how these companies are reducing their security exposure through automated data-centric protection of sensitive data in Hadoop.
Cloudera GoDataFest Security and GovernanceGoDataDriven
The document discusses Cloudera's security and governance solutions for Hadoop. It describes how Cloudera provides comprehensive security through authentication, authorization, auditing, and compliance features. It also covers how Cloudera helps with data visibility and governance through tools that report on data usage and lineage. The overall goal is to help customers securely manage and govern their data on Hadoop clusters.
The document discusses the risks associated with big data technologies and provides recommendations for securing Hadoop clusters in an enterprise environment. It notes that new technologies introduce new vulnerabilities from things like open source code and lack of security practices. It recommends implementing authentication, authorization, auditing, encryption, and other security controls in a comprehensive manner integrated within the Hadoop platform to securely enable analytics on regulated data while meeting compliance requirements.
Cloudera Navigator provides integrated data governance and security for Hadoop. It includes features for metadata management, auditing, data lineage, encryption, and policy-based data governance. KeyTrustee is Cloudera's key management server that integrates with hardware security modules to securely manage encryption keys. Together, Navigator and KeyTrustee allow users to classify data, audit usage, and encrypt data at rest and in transit to meet security and compliance needs.
Combat Cyber Threats with Cloudera Impala & Apache HadoopCloudera, Inc.
Learn how you can use Cloudera Impala to:
- Operate with all data in your domain
- Address cyber security analysis and forensics needs
- Combat fraud, waste, and abuse
Get Started with Cloudera’s Cyber SolutionCloudera, Inc.
Cloudera empowers cybersecurity innovators to proactively secure the enterprise by accelerating threat detection, investigation, and response through machine learning and complete enterprise visibility. Cloudera’s cybersecurity solution, based on Apache Spot, enables anomaly detection, behavior analytics, and comprehensive access across all enterprise data using an open, scalable platform. But what’s the easiest way to get started?
Join Cloudera, StreamSets, and Arcadia Data as we show you first hand how we have made it easier to get your first use case up and running. During this session you will learn:
Signs you need Cloudera’s cybersecurity solution
How StreamSets can help increase enterprise visibility
Providing your security analyst the right context at the right time with modern visualizations
3 things to learn:
Signs you need Cloudera’s cybersecurity solution
How StreamSets can help increase enterprise visibility
Providing your security analyst the right context at the right time with modern visualizations
As more organizations implement cloud strategies and technologies, the volume of data being transmitted to and from the cloud increases – data that must be protected. Security monitoring for threats, compromise or data theft within cloud-based applications has been difficult to achieve without the use of VM-based monitoring agents, but this is changing. Fidelis Network® Sensors coupled with Netgate TNSR™ can provide an easy-to-deploy cloud mirror port for traffic visibility, threat detection, and data loss and theft detection.
If you currently have AWS-based applications or are considering hosting applications in AWS, watch this recorded webinar to find out how Fidelis and Netgate can support the security of your cloud-based data via a high-speed cloud mirror port.
In this webinar, we discuss:
- The cloud environment and the state of cloud security today
- The technology and the integration capabilities of Netgate TNSR and Fidelis Network
- The benefits of deploying Fidelis Network sensors in the cloud no reconfiguring of applications required
The document discusses data access security in Hadoop, including Apache Sentry and RecordService. It provides an overview of Sentry, describing how it works with different Hadoop components like Hive and Impala to provide role-based access control. It also discusses the need for fine-grained access control and how RecordService aims to address this need.
This document discusses the challenges of trust, visibility and governance in Apache Hadoop and how Cloudera Navigator addresses them. It describes how Navigator provides an integrated data management and governance platform for Hadoop by collecting and integrating technical metadata, business metadata, lineage, policies and audit logs. This platform enables self-service discovery and analytics for data scientists and BI users, usage-driven optimization for Hadoop administrators and compliance capabilities for security teams. The document provides examples of the types of metadata, lineage and audit logs collected in Hadoop and their limitations, and argues that Navigator is needed to make this information actionable through policies and a governance framework.
Many solutions in the DLP marketplace today are more focused on monitoring and alerting when data has been leaked rather than preventing the actual leak. To ensure adequate protection of sensitive digital assets, it is imperative to implement a solution that not only identifies but prevents a leak before it occurs.
Ensure the security of digital assets with a full-featured network DLP solution.
With Fidelis Network®, you can block network data exfiltration in the present and look back in time to understand where, when, and how these exfiltration attempts took place and what systems were compromised.
The Document provides an overview of
the key security challenges in Big Data (Apache Hadoop)systems, and showcases the solutions used by Hortonworks Distribution to solve these security challenges.
Get started with Cloudera's cyber solutionCloudera, Inc.
Cloudera empowers cybersecurity innovators to proactively secure the enterprise by accelerating threat detection, investigation, and response through machine learning and complete enterprise visibility. Cloudera’s cybersecurity solution, based on Apache Spot, enables anomaly detection, behavior analytics, and comprehensive access across all enterprise data using an open, scalable platform. But what’s the easiest way to get started?
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.
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!
❻❸❼⓿❽❻❷⓿⓿❼KALYAN MATKA CHART FINAL OPEN JODI PANNA FIXXX DPBOSS MATKA RESULT MATKA GUESSING KALYAN CHART FINAL ANK SATTAMATAK KALYAN MAKTA SATTAMATAK KALYAN MAKTA
This presentation is about health care analysis using sentiment analysis .
*this is very useful to students who are doing project on sentiment analysis
*
19. 19
Machine Learning
19
Real-time large-scale
machine learning predictive
analytics infrastructure build
on Hadoop
• Collaborative filtering and
recommendation
• Classification and
regression,
• Clustering
Editor's Notes
Data is valuable both as asset and to your customers. As the guardians of your customers’ data, you provide services using that data such bank accounts and online tax disks. Of course you need to defend that data on your customer behalf if you want to maintain their loyalty. This talk will explore how using Cloudera’s Enterprise Data Hub you can do that, but also how you can use this technology to also play some offence and use the immense computational power to evaluate how you customer are being subject to cyber attacks and how you can help them.
In the same way that data is indicative to business about purchase behavior and intent. So it is valuable to the bad guys whether to damage reputation, or simply to trade. The bad guys have the advantage of being able to aggregate from numerous data sources without worrying about regulation other than getting caught. As business moves their assets and knowledge capital online, these asset are increasingly spread throughout the supply chain business. For large enterprises protective this supply chain is challenging especially where it is outsourced
Multi-tenant secure clusters running EDH could be the solution, resources are pooled together to create capability whereby all of the instrumentation and data assets are stored in the same data lake or reservoir, partitioned by robust security.
Let’s take a look at some typical security layers that are used to protect these assets.
Cloudera Enteprise Data Hub provides enterprise class security for Hadoop to specifically to enable complex and challenging regulatory workloads. Incorporating many upstream features from Intel’s project Rhino including encryption at rest and in motion with hardware enhanced performance, better use of role based access control, high levels of granularity such as cell level access control in Hbase and end to end audit compliance.
YARN Static and Dynamic resource pools restrict resource utilization in a shared multi-tenant environment, thus contributing to availability of the cluster
Encryption ensures the integrity and indeed the confidentiality of the data
All communications including remote procedure calls between nodes for are authorized with a valid ticket. The KDC may feature a one way trust with the corporate directory or indeed be fully integrated using SSSD
Role based access control to underlying data facilitate multi tenant (within the Enterprise) access to data
Tracking the provenance of your data, throughout storage and processing chain is vital particularly if that data is subject to compliance regulation such as PCI
Why you need Navigator:
Lots of Data Landing in Cloudera Enterprise
Huge quantities
Many different sources – structured and unstructured
Varying levels of sensitivity
Many Users Working with the Data
Administrators and compliance officers
Analysts and data scientists
Business users
Need to Effectively Control and Consume Data
Get visibility and control over the environment
Discover and explore data
Encryption in motion, SSL enabled for services with authenticated RPC calls on the cluster. The key trustee server can be integrated with existing HSMs in order that the master encryption keys be both tamper proof and revokable and work with existing key management policies. The access controls are processed based which effectively prevents a root user access to the unencrypted contents of a file. An important and valuable separation of duties.
Our design strategy is to tightly integrate different processing paradigms into the Hadoop system. Resources are pooled enable different computation workloads such Map Reduce and Impala to utilize common infrastructure. Interactive SQL, batch processing whether map reduce, spark or stream processing such as Spark streaming are just another applications that you bring to your data. These are integrated with Hadoop’s existing security and resource management frameworks and is completely interoperable with existing data formats and processing engines such as Map Reduce.
One pool of data
Storage platforms (HDFS & HBase)
Open data formats (files & records)
Shared across multiple processing frameworks
One metadata model
No synchronization of metadata between 2 different systems (analytical DBMS and Hadoop)
Same metadata used by other components within Hadoop itself (Hive, Pig, Impala, etc.)
One security framework
Single model for all of Hadoop
Doesn’t require “turning off” any portion of native Hadoop security
One set of system resources
One set of nodes – storage, CPU, memory
One management console
Integrated resource management
Scale linearly as capacity or performance needs grow
The Enterprise data hub infrastructure can support an array of user cases that would otherwise be locked in expensive limited capability silos. Those user cases can be applied to the full data set more productively, at lower costs. As a result the economics facilitate the overall capability to ask those bigger questions. These user cases apply across domains encompassing management, security, HR and business intelligence.
Complex Map Reduce jobs are often a chained series of task that involve Maps Reduce Maps Maps Reduce and so on. Apache Spark significantly simplifies the coding of these complex pipelines with a common API for both batch and streaming the programmer can then explicitly write to disk at the most optimum time
Enterprises are increasingly using Hadoop and the economics of BigData to drive efficiencies in the way they provide and consume IT services. BigData economics allow the entirety of both the structured management metrics from IT infrastructure to be combined with the unstructured supporting commentary.
This allows for new types of exploitation such as machine learning and predictive analysis. The innovation begins with continuously ingesting the metrification and supporting commentary that is describing the current performance. Discovery evaluates the historical patterns of performance that build up over time using machine learning to construct a model. These patterns in turn provide the insights into the predictions that those signals often illustrate. Cases include variations in efficiencies of manufacturers disks for variable such as power consumption, developer team code performance, impact of training and certification. All of which enables further innovations and gains based on facts.
Flume
A resilient framework for delivering event data to the Hadoop cluster. Sources, Channels and Sinks
Kite is a set of libraries tools and features to build Hadoop applications
Morphlines provides configuration driven tools that can extract facets using interceptors on the ingestion pipeline to enrich with meta data records
In this sample all of the Apache web server logs are filtered for http 408 errors. The faceting by country using geoip lookup helps identify the source of the DDOS
Slowloris is an Old DDOS trick whereby a web client very slooowly makes a connection to the web server, assuming Apache is patched the slowloris is revealed by filtering on the 408 errors.
It can continuously build models from a stream of data at large scale using Apache Hadoop. It also serves queries of those models in real-time via an HTTP REST API, and can update models approximately in response to streaming new data. This two-tier design, comprised of the Computation Layer and Serving Layer, respectively, implement a lambda architecture. Collaborative filtering works like people that search for this search for that. Collaborative filtering is a form of supervised learning, where a value is predicted for new inputs based on known values for previous inputs often used for Spam filers. Clustering will group using algorithms such as Kmeans based on common features.
Vectorising using TF-IDF for term frequency inverse document frequency which infers how important a word might be in a document. These can then be classified using an algorithm such as Naïve bayes
Useful to extract as a feature that can then be clustered using Kmeans across a corpus of documents. Often used by search engines to score and rank documents according to a query. So for example stream of data from a Twitter channel sharing a hash tag
Choices Oryx 1 Map Reduce based, Oryx 2 Spark based and Spark Mlib
Doing so in memory on Spark is good for iterative algorithms avoid the need to materialize the data and jobs such as monte carlo simulations