

Bill Hughes is a former professor of marketing at Kellogg School of Management. The author of Windows Phone 7 For Dummies, Bill has worked with major corporations including IBM, Motorola, and Nextel.
Meer over Bill HughesAgile Data Warehousing Project Management
Business Intelligence Systems Using Scrum
Samenvatting
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
- Offers a step-by-step introduction to defining, planning, and delivering an agile data warehouse
- Enables you and your teams to start simple and progress steadily to world-class performance levels
Specificaties
Inhoudsopgave
List of tables
Preface
Author's Bio
Part 1: A Generic Agile Method
1. Why Agile?
-The "Disappointment Cycle" of Many Traditional Projects
-Agile's Iterative and Incremental Delivery Alternative
-Agile as Applied to Data Warehousing
-Not A Revolution, Just An Impressive Evolution
-Where to Be Cautious with Agile DW/BI
2. Agile Development in a Nutshell
-Minimal Facilities Required
-Product Owners and Scrum Masters
-Three Cycles of a Generic Scrum Iteration
-Iteration Phase 1: Story Conferences
-Iteration Phase 2: Task Planning
-Iteration Phase 3: Development Phase
-Iteration Phase 4: User Demos
-Iteration Phase 5: Sprint Retrospectives
-Non-Standard Iterations
3. Project Management Lite
-Highly-Transparent Task Boards
-Burndown Charts Reveal Progress and Velocity
-Dealing with Tech Debt and Scope Creep
-Should You Extend a Sprint?
-Overcoming Geographical Barriers
4. User Stories for Business Intelligence Applications
-Traditional Requirement Management And Its Discontents
-Agile's Idea of "User Stories"
-User Story Definition Fundamentals
-Generic Frameworks for Writing Good User Stories
Part 2: Adapting Agile to Data Warehousing
5. Developer Stories for Data Integration Projects
-Warehousing Architecture and "Developer Stories"
-Better Warehouse User Epic Decomposition
-Further Project Partitioning Strategies
-Answering the Nay Sayers
6. Agile Estimation for DW/BI
-The Damage Done By Bad Estimation
-Why Waterfall Estimate Poorly
-Two Approaches: Story Points Versus Ideal Time
-Agile Estimation Techniques
-Agile Release and Project Planning
-Estimation Quality As The Team's One, True Metric
7. Further Adaptations for Agile Data Warehousing
-Additional Roles Required
-Scrumban: Pipelined Delivery Yields a Sustainable Pace
-Tiered Data Models for Managing Dependencies
-Reference Models and BOE Cards
-Balancing Agility and Perfection in Design
-Demo Data Churn and Its Solutions
-Communicating Progress
-The Agile Data Warehousing Manifesto
8. Starting and Scaling Agile Warehousing Teams
-Six Stages in Nurturing A World-Class Team
-Stage 0: Time-Boxed Iterations & Agile Estimation
-Stage 1: Release Planning
-Stage 2: Pipelined Delivery Squads
-Stage 3: Requirements Decomposition
-Stage 4: Reference Models & Test-Led Development
-Stage 5: Continuous Integration Testing
-Managing Frustration with Early Iterations
-Managing Adversity within the Larger Organization
-Picking velocities for the first sprint
-Scaling Scrum Teams
-SideBar: Items for Iteration -1 and 0
Part 3: Retrospective
9. Faster, Better, Cheaper
-What is Agile?
-What is Agile Data Warehousing?
-Where Does Agile Get All Its Speed?
-Why does Agile Work So Well?
-Answering the What Abouts?
References
Index
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