Agile Data Warehousing Project Management

Agile Data Warehousing Project Management

Business Intelligence Systems Using Scrum

1st Edition - September 28, 2012

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  • Author: Ralph Hughes
  • eBook ISBN: 9780123965172
  • Paperback ISBN: 9780123964632

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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 writing good user stories

    Summary

    Chapter 5. Deriving Initial Project Backlogs

    Value of the initial backlog

    Sketch of the sample project

    Fitting initial backlog work into a release cycle

    The handoff between enterprise and project architects

    User role modeling results

    Key persona definitions

    Carla in corp strategy

    An example of an initial backlog interview

    Finance is upstream

    Observations regarding initial backlog sessions

    Summary

    Chapter 6. Developer Stories for Data Integration

    Why developer stories are needed

    Introducing the “developer story”

    Developer stories in the agile requirements management scheme

    Agile purists do not like developer stories

    Initial developer story workshops

    Data warehousing/business intelligence reference data architecture

    Forming backlogs with developer stories

    Evaluating good developer stories: DILBERT’S test

    Secondary techniques when developer stories are still too large

    Summary

    Chapter 7. Estimating and Segmenting Projects

    Failure of traditional estimation techniques

    An agile estimation approach

    Quick story points via “estimation poker”

    Story points and ideal time

    Estimation accuracy as an indicator of team performance

    Value pointing user stories

    Packaging stories into iterations and project plans

    Segmenting projects into business-valued releases

    Project segmentation technique 1: dividing the star schema

    Project segmentation technique 2: dividing the tiered integration model

    Project segmentation technique 3: grouping waypoints on the categorized services model

    Embracing rework when it pays

    Summary

    Part 3: Adapting Iterative Development for Data Warehousing Projects

    Chapter 8. Adapting Agile for Data Warehousing

    The context as development begins

    Data warehousing/business intelligence-specific team roles

    Avoiding data churn within sprints

    Pipeline delivery for a sustainable pace

    Continuous and automated integration testing

    Evolutionary target schemas—the hard way

    Summary

    Chapter 9. Starting and Scaling Agile Data Warehousing

    Starting a scrum team

    Scaling agile

    What is agile data warehousing?

    Communicating success

    Moving to pull-driven systems

    Summary

    References

    Chapter 1

    Chapter 2

    Chapter 3

    Chapter 4

    Chapter 5

    Chapter 6

    Chapter 7

    Chapter 8

    Chapter 9

    Index

Product details

  • No. of pages: 366
  • Language: English
  • Copyright: © Morgan Kaufmann 2012
  • Published: September 28, 2012
  • Imprint: Morgan Kaufmann
  • eBook ISBN: 9780123965172
  • Paperback ISBN: 9780123964632

About the Author

Ralph Hughes

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

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