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.

Data Management A Comprehensive Overview illustrates the essential concepts which support master data management (MDM) strategies and the ability to build advanced data capabilities such as AI and advanced analytics.

This course will help you understand data management, the impact it can have in an organization, and ensure that organizational data priorities can be understood and applied in a practical way. Specifically, this course focuses on understanding how to collect, prepare, store, use and manage data so it’s well-suited to AI, machine learning applications, and advanced analytics and data life cycle strategies.

Learn enterprise data management based on understanding the data life cycle

To manage data, you must break down the overall life cycle of data into different stages, then examine how each stage gets managed. It's a “cradle to grave” approach to working with data. This course teaches all the aspects of the data life cycle... how it comes into the organization, how you work with it, and how you decide what data should and shouldn't come into the organization. You’ll learn how to manage change, share, and secure data – and determine when data should be removed or destroyed.

Public Classroom Pricing


GSA Price: $195

Group Rate: $195

Private Group Pricing

Have a group of 5 or more students? Request special pricing for private group training today.

Part 1: Overview – What is Data Management?

  • Why we need data management
  • Data as an organizational asset
  • What’s at stake
  • Who’s affected
  • Prioritizing data assets
  • Managing data through its life cycle
  • How data relates to AI

Part 2: Understanding strategic data priorities

  • Vision and focus for data strategy
  • Guiding principles for managing data
  • How strategy relates to management

Part 3: Understanding the data life cycle

  • Overview of the data life cycle
  • Plan
  • Collect
  • Assure
  • Describe
  • Preserve
  • Use
  • Integrate
  • Analyze
  • Dispose

Part 4: Managing data life cycle stages

  • The value of managing life cycle stages
  • Manage for planning
  • Manage for collection
  • Data quality and integrity
  • Manage for assurance and quality
  • Data cleansing and transformation
  • Manage for description
  • Manage for preservation and storage
  • Manage for usage
  • Manage for integration
  • Manage for analysis
  • Manage for disposal

Part 5: Managing across the life cycle

  • Design
  • Architecture
  • Storage
  • Governance
  • Stewardship
  • Security
  • Privacy
  • Administration and maintenance
  • Change management

Part 6: Course conclusion

  • Revisiting data management goals
  • Why data is such an important asset
  • Why a data management strategy depends on mission objectives

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

After you complete this course, you will be able to:

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

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