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A Complete Set of Data Governance Roles & Responsibilities

KIK Consulting

Roles and responsibilities are the backbone to a successful Data Governance program. The way you define and utilize the roles will be the biggest factor of program success. From Data Stewards to the steering committee and everyone in between, people will need to understand the role they play, why they are in the role and how the role fits in with their existing job. Join Bob Seiner for this RWDG webinar where he will provide a complete and detailed set of Data Governance roles and responsibilities. Bob will share an Operating Model of Roles and Responsibilities that can be customized to address the specific needs of your organization
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Understanding User Entity and Behavior Analytics (UEBA)

User Entity and Behavior Analytics (UEBA) is a cybersecurity technology and approach that focuses on analyzing the behavior of users and entities (such as devices, applications, and systems) within an organization's IT environment. By using advanced data analytics, machine learning algorithms, and artificial intelligence, UEBA aims to detect and prevent cyber threats by identifying anomalies, deviations, or patterns in user and entity activities that might indicate potential security risks.

OTHER ON-DEMAND WEBINARS

Build an Effective Data Governance Framework

DATAVERSITY

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.
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Automated Data and Analytics Workload Modernization

Moving on-premises legacy data and analytics workloads to the cloud is unavoidable if you want to overcome infrastructural constraints, facilitate proactive analytics, and lower costs. You need a service that enables seamless scalability for petabyte-scale data processing, interactive analytics, and machine learning. However, end-to-end, automated workload transformation and optimization on serverless services is not straightforward.
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Modernizing the Legacy Data Warehouse – What, Why, and How

cloudera

The Eckerson Group's Dave Wells and Cloudera's Eva Nahiri share the challenges of legacy data warehousing, the goals of modern data warehousing, and the design patterns and frameworks that help to accelerate modernization efforts.
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IBM Data Science Community

As enterprises become more agile, centralization appears more and more a thing of the past waterfall world. This need is equally true with data platforms. This paradigm drove us to build a Data Mesh, this next generation of data platforms for PayPal Credit. This talk will detail quickly go over the evolution of data platforms, highlight the problems of current data platforms, and explain why we decided to build a Data Mesh. I will detail the four principles of the Data Mesh, how we got started, and describe some current and future challenges and how we plan to solve them. Part of the Expert Hour series.
Watch Now

Build an Effective Data Governance Framework

DATAVERSITY

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.
Watch Now

Automated Data and Analytics Workload Modernization

Moving on-premises legacy data and analytics workloads to the cloud is unavoidable if you want to overcome infrastructural constraints, facilitate proactive analytics, and lower costs. You need a service that enables seamless scalability for petabyte-scale data processing, interactive analytics, and machine learning. However, end-to-end, automated workload transformation and optimization on serverless services is not straightforward.
Watch Now

Modernizing the Legacy Data Warehouse – What, Why, and How

cloudera

The Eckerson Group's Dave Wells and Cloudera's Eva Nahiri share the challenges of legacy data warehousing, the goals of modern data warehousing, and the design patterns and frameworks that help to accelerate modernization efforts.
Watch Now

IBM Data Science Community

As enterprises become more agile, centralization appears more and more a thing of the past waterfall world. This need is equally true with data platforms. This paradigm drove us to build a Data Mesh, this next generation of data platforms for PayPal Credit. This talk will detail quickly go over the evolution of data platforms, highlight the problems of current data platforms, and explain why we decided to build a Data Mesh. I will detail the four principles of the Data Mesh, how we got started, and describe some current and future challenges and how we plan to solve them. Part of the Expert Hour series.
Watch Now
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Understanding User Entity and Behavior Analytics (UEBA)

User Entity and Behavior Analytics (UEBA) is a cybersecurity technology and approach that focuses on analyzing the behavior of users and entities (such as devices, applications, and systems) within an organization's IT environment. By using advanced data analytics, machine learning algorithms, and artificial intelligence, UEBA aims to detect and prevent cyber threats by identifying anomalies, deviations, or patterns in user and entity activities that might indicate potential security risks.

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