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Agile Data Warehousing Project Management
 
 

Agile Data Warehousing Project Management, 1st Edition

Business Intelligence Systems Using Scrum

 
Agile Data Warehousing Project Management, 1st Edition,Ralph Hughes,ISBN9780123964632
 
 
 

  

Morgan Kaufmann

9780123964632

9780123965172

366

235 X 191

The only step-by-step guide to visualizing, building, and validating an agile enterprise data warehouse

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Key Features

* 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

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.

Readership

data warehousing professionals including architects, designers, data modelers, testers, database administrators, programmers, developers, scrum masters and project managers as well as IT managers, directors, and VPs

Ralph Hughes

Ralph Hughes, former DW/BI practice manager for a leading global systems integrator, has led numerous BI programs and projects for Fortune 500 companies in aerospace, government, telecom, and pharmaceuticals. A certified Scrum Master and a PMI Project Management Professional, he began developing an agile method for data warehouse 15 years ago, and was the first to publish books on the iterative solutions for business intelligence projects. He is a veteran trainer with the world's leading data warehouse institute and has instructed or coached over 1,000 BI professionals worldwide in the discipline of incremental delivery of large data management systems. A frequent keynote speaker at business intelligence and data management events, he serves as a judge on emerging technologies award panels and program advisory committees of advanced technology conferences. He holds BA and MA degrees from Stanford University where he studied computer modeling and econometric forecasting. A co-inventor of Zuzena, the automated testing engine for data warehouses, he serves as Chief Systems Architect for Ceregenics and consults on agile projects internationally.

Affiliations and Expertise

former DW/BI practice manager for a leading global systems integrator, has led numerous BI programs and projects for Fortune 500 companies in aerospace, government, telecom, and pharmaceuticals.

Agile Data Warehousing Project Management, 1st Edition

Part I: A Generic Agile Method
Chapter 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

Chapter 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

Chapter 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

Chapter 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 II. Adapting Agile to Data Warehousing
Chapter 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

Chapter 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

Chapter 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

Chapter 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 III. Retrospective
Chapter 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?

Quotes and reviews

"Anyone who has worked on a data warehousing project knows that it can be a monumental undertaking. Agile Data Warehouse (sic) Project Management…offers up an approach that can minimize challenges and improve the chance of successful delivery."--Data and Technology Today blog, April 23, 2013
"Hughes first began working with agile data warehousing in 1996 and received skeptical reactions up until at least six years ago. Having stuck with this approach throughout, he is now receiving a more and more favorable reception and here uses his expertise to deliver a thorough implementation guide."--Reference and Research Book News, December 2012

 
 
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