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Basic Data Management – A Comprehensive Overview eLearning

A walkthrough of enterprise data management, covering the knowledge and key terms you need to understand how data is managed throughout its life cycle.

Overview

This course covers the data life cycle from cradle to grave, learns about management priorities for every phase of the life cycle, and develops overall literacy on handling data as a strategic asset. This course emphasizes data management practices that tie to AI and machine learning applications.

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$25 (USD)
Group (3+): $25 USD
GSA: $18.25 USD
Education Credits:
3 PDUs
0.5 Leadership PDUs
1.5 Strategy PDUs
1 Technical PDUs
1 PBA PDUs
1 RMP PDUs
1 PFMP PDUs
3 PDUs

Next Upcoming Course

There are currently no scheduled classes for this course.
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Full Course Details

Part 1: Understanding what data management is and why it is an important asset

  • Why we need data management
  • Who and what is impacted by data
  • Data as an organizational asset

Part 2: Understanding strategic data priorities

  • Prioritize data assets 
  • What’s at stake if we fail to properly manage data?
  • How data relates to AI

Part 3: Data Strategy

  • Seven goals
  • Guiding Principles

Part 4: Overview of the Data Lifecycle

  • Phases of the lifecycle
  • Data Framework

Part 5: Where Data Management Fits

  • Manage for planning
  • Planning key questions
  • Collect key data and questions
  • Developing a quality insurance plan

Part 6: Manage Across the Lifecycle

  • What is data architecture? 
  • What is data governance? 
  • Core data stewardship concepts 
  • Data security and privacy

Part 7: Final Assessment

This Basic Data Management self-paced course will be invaluable for:

  • Data strategy owners
  • Data managers
  • Data engineers
  • Artificial intelligence stakeholders
  • Database administrators
  • Digital transformation leaders
  • Data integrators

  • Understand why data is such an important asset
  • Review who and what is impacted by data
  • Why data management facilitates a culture of better data-driven decisions
  • Examine the data lifecycle and each of its phases
  • Learn how to manage data based on the phases of its lifecycle
  • Understand data management priorities that transcend individual phases of its lifecycle
  • Collect. Prepare, store, use, and manage data so it’s well-suited to AI ad machine learning applications
  • Learn why a data management strategy depends on mission objectives

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