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.

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

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

Table of Contents

List of Figures

List of Tables

Preface

Answering the skeptics

Intended audience

Parts and chapters of the book

Invitation to join the agile warehousing community

Author’s Bio

Part 1: An Introduction to Iterative Development

Chapter 1. What Is Agile Data Warehousing?

A quick peek at an agile method

The “disappointment cycle” of many traditional projects

The waterfall method was, in fact, a mistake

Agile’s iterative and incremental delivery alternative

Agile for data warehousing

Where to be cautious with agile data warehousing

Summary

Chapter 2. Iterative Development in a Nutshell

Starter concepts

Iteration phase 1: story conferences

Iteration phase 2: task planning

Iteration phase 3: development phase

Iteration phase 4: user demo

Iteration phase 5: sprint retrospectives

Close collaboration is essential

Selecting the optimal iteration length

Nonstandard sprints

Where did scrum come from?

Summary

Chapter 3. Streamlining Project Management

Highly transparent task boards

Burndown charts reveal the team aggregate progress

Calculating velocity from burndown charts

Common variations on burndown charts

Managing miditeration scope creep

Diagnosing problems with burndown chart patterns

Should you extend a sprint if running late?

Should teams track actual hours during a sprint?

Managing geographically distributed teams

Summary

Part 2: Defining Data Warehousing Projects for Iterative Development

Chapter 4. Authoring Better User Stories

Traditional requirements gathering and its discontents

Agile’s idea of “user stories”

User story definition fundamentals

Common techniques for wri

Details

No. of pages:
366
Language:
English
Copyright:
© 2013
Published:
Imprint:
Morgan Kaufmann
eBook ISBN:
9780123965172
Print ISBN:
9780123964632

About the author

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

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 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