Data Life Cycle Management | Cprime Learning | Data Life Cycle








Data Life Cycle Management

Learn the fundamental processes and best practices to develop a data life cycle management plan for your organization.


Managing business information through its life cycle from requirements through retirement is the data lifecycle management process. In order to use data to support business goals with minimal risk, managing information properly over its lifetime equips organizations with the right information. The vast amounts of data, and growing, that businesses must understand underpins the emergent notion that organizations must put appropriate processes into place for effective data lifecycle management.

In this three-day course, you will dig through fundamental data management processes, best practices, and methods that enable you to develop a data management plan for your organization. Not only will you be able to develop an effective data management plan, you will go back to work with the practices and methods to effectively create, organize, manage, preserve, and share data. By having the right skills, processes, and practices you will be able to address the organizational challenges of reducing risk, costs, and increasing organizational responsiveness. 

Reserve Your Seat
$1995 (USD)
3 days/24 hours of instruction
Group (3+): $1725 USD
GSA: $1496.25 USD
Education Credits:
21 PDUs
7 Strategy PDUs
14 Technical PDUs
21 PDUs

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There are currently no scheduled classes for this course. Please contact us if you would like more information or to schedule this course for you or your company.

Full Course Details

Part 1: Introduction to Life Cycle Management

  1. Recognizing the vital stages in the start to end life cycle of data and storage Architectures
    1. Understand why it is important to manage data
    2. Understand and explore the stages in the data lifecycle
      1. Plan, Collect, Assure, Describe, Preserve, Discover, Integrate, Analyze
    3. Understand the key storage architectures
    4. Distinguish the pros/cons of using different architectures
    5. Exercise: Practice identifying elements of data life cycle and their function
    6. Exercise: Practice identifying storage architectures and their appropriate use
  2. Importance of architecture, analysis, and design
    1. Differentiate between core architectures
    2. Understand the importance of analysis and how to use it to guide data management decisions
    3. Understand strategies for translating analysis and design
    4. Exercise: Identifying architectures
    5. Exercise: Practice analysis process and design process
  3. Recognize data as a key business asset
    1. Identify data as a business asset
    2. Learn to prioritize data assets
    3. Exercise: Identifying key business data
    4. Exercise: Prioritizing data
  4. Stewardship and governance of data Through the Lifecycle
    1. Core Data Stewardship Concepts
    2. Data quality, integrity, accessibility and security
    3. Core elements of a data governance plan
    4. Data protection, risk assessment, compliance requirements, stakeholder management and access management
    5. Exercise: Identifying data governance principles
    6. Exercise: Identifying data stewardship principles

Part 2: Database Design

  1. Designing provisioning workflows
    1. Explore principles of Agile Provisioning
    2. Inspect provisioning workflows
    3. Provisioning best practices
  2. Data cleansing and transformation
    1. Principles of data cleansing and data transformation
    2. Data cleansing best practices
    3. Data transformation planning
    4. Exercise: Design provisioning workflows
    5. Exercise: Develop data cleansing and transformation plans
  3. Designing patching workflows
    1. Core elements of developing a patch plan
    2. Implications of a poorly designed patch workflow
    3. Patch management best practices
  4. Ensuring the quality and integrity of data
    1. Fundamentals of quality and integrity in data
    2. Data quality best practices
    3. Data integrity best practices
    4. Exercise: Design patching workflows
    5. Exercise: Practice data quality and integrity planning
  5. Data security and management
    1. Best practices in data security management
    2. Approaches to privacy management
    3. Data security and privacy management planning
  6. Provisioning new databases from reference systems
    1. Analyzing reference systems for requirements
    2. Considerations when developing a provisioning plan from reference systems
    3. Exercise: Analyze security and privacy management plans
    4. Exercise: Practice provisioning from reference systems

Part 3: Configuration and Change Management

  1. Defining a gold standard and baseline configuration
    1. Explore data standard best practices
    2. Examine considerations for a baseline data configuration
    3. Learn core aspects of a solid data development methodology
  2. Change activity planning
    1. Plan Change Activity, including starting and end dates; creating assigning and tracking task status
    2. Learn to manage large numbers of task and targets
    3. Learn to monitor your plans for potential delays and quickly evaluate overall plan status
    4. Exercise: Best Practices in standards and baseline configurations
    5. Exercise: Change Activity Planning
  3. Patch management
    1. Learn the core elements of a patch management process
      1. Detect
      2. Assess
      3. Acquire
      4. Test
      5. Deploy
      6. Maintain
    2. Monitoring vulnerabilities, remediation’s and threats
  4. Pre-deployment analysis
    1. Learn core elements of a pre-deployment plan
    2. Best practices in pre-deployment analysis
    3. Exercise: Practice analyzing patch management plans
    4. Exercise: Practice analyzing pre-deployment analysis
  5. Managing the rollout
    1. Foundations of a successful roll-out plan
    2. Potential pitfalls that affect roll-outs
    3. Explore steps in a standard roll-out plan
  6. Reporting status and conflict resolution
    1. Strategies for status reporting
    2. Core techniques in conflict resolution
    3. Best practices with regards to conflict resolution
    4. Explore components of a conflict resolution plan
    5. Exercise: Practice analyzing roll-out plans, status reporting plans, and conflict resolution plans

Part 4: Compliance Management

  1. Compliance standards
    1. Core elements of compliance standards
    2. Work towards a compliance framework
    3. Examine compliance standards rules
    4. Exercise: Practice analyzing compliance standards
    5. Exercise: Practice analyzing the elements of a compliance framework
    6. Exercise: Practice developing conceptual compliance standards rules
  2. Security and configuration reporting best practices
    1. Best practices in security reporting
    2. Best practices in configuration reporting
    3. Exercise: Practice analyzing security reporting methods
    4. Exercise: Practice analyzing configuration reporting methods
  3. Detecting unauthorized changes
    1. Principles of data auditing and DAM (Database Activity Monitoring)
    2. Explore common techniques for data auditing within databases
    3. Examine database logs for unauthorized changes
    4. Developing policies to manage unauthorized access
    5. Exercise: Practice applying database activity monitoring principles
    6. Exercise: Practice examining database logs
    7. Exercise: Practice developing access policies

Part 5: Disaster Protection

  1. Building for availability
    1. System design considerations for availability
    2. Overview of high available methodologies
    3. Explore available design and management best practices
    4. Exercise: Practice analyzing system design considerations
    5. Exercise: Practice analyzing high availability methodologies
    6. Exercise: Practicing analyzing availability design and management best practices
  2. Automating a complete site failover
    1. Core principles in automating a complete site failover
    2. Site failover automation methodologies
    3. Best practices in automation of complete site failover
    4. Exercise: Practice analyzing core principles of automating a complete site failover
    5. Exercise: Practice distinguishing between site failover automation methodologies
    6. Exercise: Practice identifying best practices
  3. Minimizing risk
    1. Core concepts in data risk management
    2. Fundamental elements of a data risk management plan
    3. Data risk management best practices
    4. Exercise: Practice identifying core concepts in data risk management
    5. Exercise: Practice developing elements of a data risk management plan
    6. Exercise: Practice identifying best practices

This course is appropriate for anyone interested in data management. There are no prerequisites for this class, however, it is recommended students come prepared knowing how data in their current organization is managed.

Professionals who benefit from this course include:

  • Data Managers
  • Data Management Analysts
  • Database Administrators
  • Data Architects
  • Data Scientist
  • Business Analysts
  • Business managers and leaders
  • PMO Managers
  • CIO, CTO, Directors of IT

  • Develop a data life cycle management plan for your organization
  • Create, organize, manage, preserve, and share data with key stakeholders
  • Determine best practices and methods to reduce risk and cost.
  • Identify storage architectures and their appropriate use
  • Identify key business data and make crucial decisions
  • Develop data cleansing and transformation plans
  • Analyze security and privacy management for your organization's data
  • Configure reporting methods

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