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Agile Data Warehousing Project Management

Agile Data Warehousing Project Management

by Ralph Hughes
Publisher: Morgan Kaufmann
Release Date: December 2012
ISBN: 9780123964632
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Book Description

You have to make sense of enormous amounts of data, and while the notion of “agile data warehousing” might sound tricky, it can yield as much as a 3-to-1 speed advantage while cutting project costs in half. Bring this highly effective technique to your organization with the wisdom of agile data warehousing expert Ralph Hughes.

Agile Data Warehousing Project Management will give you a thorough introduction to the method as you would practice it in the project room to build a serious “data mart.” Regardless of where you are today, this step-by-step implementation guide will prepare you to join or even lead a team in visualizing, building, and validating a single component to an enterprise data warehouse.

  • Provides a thorough grounding on the mechanics of Scrum as well as practical advice on keeping your team on track
  • Includes strategies for getting accurate and actionable requirements from a team’s business partner
  • Revolutionary estimating techniques that make forecasting labor far more understandable and accurate
  • Demonstrates a blends of Agile methods to simplify team management and synchronize inputs across IT specialties
  • Enables you and your teams to start simple and progress steadily to world-class performance levels

Table of Contents

  1. Cover image
  2. Title page
  3. Table of Contents
  4. Copyright
  5. List of Figures
  6. List of Tables
  7. Preface
    1. Answering the skeptics
    2. Intended audience
    3. Parts and chapters of the book
    4. Invitation to join the agile warehousing community
  8. Author’s Bio
  9. Part 1: An Introduction to Iterative Development
    1. Chapter 1. What Is Agile Data Warehousing?
      1. A quick peek at an agile method
      2. The “disappointment cycle” of many traditional projects
      3. The waterfall method was, in fact, a mistake
      4. Agile’s iterative and incremental delivery alternative
      5. Agile for data warehousing
      6. Where to be cautious with agile data warehousing
      7. Summary
    2. Chapter 2. Iterative Development in a Nutshell
      1. Starter concepts
      2. Iteration phase 1: story conferences
      3. Iteration phase 2: task planning
      4. Iteration phase 3: development phase
      5. Iteration phase 4: user demo
      6. Iteration phase 5: sprint retrospectives
      7. Close collaboration is essential
      8. Selecting the optimal iteration length
      9. Nonstandard sprints
      10. Where did scrum come from?
      11. Summary
    3. Chapter 3. Streamlining Project Management
      1. Highly transparent task boards
      2. Burndown charts reveal the team aggregate progress
      3. Calculating velocity from burndown charts
      4. Common variations on burndown charts
      5. Managing miditeration scope creep
      6. Diagnosing problems with burndown chart patterns
      7. Should you extend a sprint if running late?
      8. Should teams track actual hours during a sprint?
      9. Managing geographically distributed teams
      10. Summary
  10. Part 2: Defining Data Warehousing Projects for Iterative Development
    1. Chapter 4. Authoring Better User Stories
      1. Traditional requirements gathering and its discontents
      2. Agile’s idea of “user stories”
      3. User story definition fundamentals
      4. Common techniques for writing good user stories
      5. Summary
    2. Chapter 5. Deriving Initial Project Backlogs
      1. Value of the initial backlog
      2. Sketch of the sample project
      3. Fitting initial backlog work into a release cycle
      4. The handoff between enterprise and project architects
      5. User role modeling results
      6. Key persona definitions
      7. Carla in corp strategy
      8. An example of an initial backlog interview
      9. Finance is upstream
      10. Observations regarding initial backlog sessions
      11. Summary
    3. Chapter 6. Developer Stories for Data Integration
      1. Why developer stories are needed
      2. Introducing the “developer story”
      3. Developer stories in the agile requirements management scheme
      4. Agile purists do not like developer stories
      5. Initial developer story workshops
      6. Data warehousing/business intelligence reference data architecture
      7. Forming backlogs with developer stories
      8. Evaluating good developer stories: DILBERT’S test
      9. Secondary techniques when developer stories are still too large
      10. Summary
    4. Chapter 7. Estimating and Segmenting Projects
      1. Failure of traditional estimation techniques
      2. An agile estimation approach
      3. Quick story points via “estimation poker”
      4. Story points and ideal time
      5. Estimation accuracy as an indicator of team performance
      6. Value pointing user stories
      7. Packaging stories into iterations and project plans
      8. Segmenting projects into business-valued releases
      9. Project segmentation technique 1: dividing the star schema
      10. Project segmentation technique 2: dividing the tiered integration model
      11. Project segmentation technique 3: grouping waypoints on the categorized services model
      12. Embracing rework when it pays
      13. Summary
  11. Part 3: Adapting Iterative Development for Data Warehousing Projects
    1. Chapter 8. Adapting Agile for Data Warehousing
      1. The context as development begins
      2. Data warehousing/business intelligence-specific team roles
      3. Avoiding data churn within sprints
      4. Pipeline delivery for a sustainable pace
      5. Continuous and automated integration testing
      6. Evolutionary target schemas—the hard way
      7. Summary
    2. Chapter 9. Starting and Scaling Agile Data Warehousing
      1. Starting a scrum team
      2. Scaling agile
      3. What is agile data warehousing?
      4. Communicating success
      5. Moving to pull-driven systems
      6. Summary
  12. References
    1. Chapter 1
    2. Chapter 2
    3. Chapter 3
    4. Chapter 4
    5. Chapter 5
    6. Chapter 6
    7. Chapter 7
    8. Chapter 8
    9. Chapter 9
  13. Index