Agile

Agile Methodology for Data Warehouse and Data Integration Projects
Karthik Kannan, Informatica Professional Services

W H I T E PA P E R

This document contains Confidential, Proprietary and Trade Secret Information (“Confidential Information”) of Informatica Corporation and may not be copied, distributed, duplicated, or otherwise reproduced in any manner without the prior written consentof Informatica. While every attempt has been made to ensure that the information in this document is accurate and complete, some typographical errors or technical inaccuracies may exist. Informatica does not accept responsibility for any kind of loss resulting from the use of information contained in this document. The information contained in this document is subject to change without notice. Theincorporation of the product attributes discussed in these materials into any release or upgrade of any Informatica software product—as well as the timing of any such release or upgrade—is at the sole discretion of Informatica. Protected by one or more of the following U.S. Patents: 6,032,158; 5,794,246; 6,014,670; 6,339,775; 6,044,374; 6,208,990; 6,208,990; 6,850,947; 6,895,471; or by thefollowing pending U.S. Patents: 09/644,280; 10/966,046; 10/727,700. This edition published August 2011

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Table of Contents
Introduction to data warehouse project management . . . . . . . . . . . . . . . . . 2 Purpose of this document . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 Agile softwaredevelopment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 Agile team structure . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 Characters involved in the development . . . . . . . . . . . . . . . . . . . . . . . . . . . 4
Pig roles . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 Chicken roles . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5

Meetings in an agile lifecycle . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5
Releaseplanning meeting . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 Daily scrum . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 Sprint planning meeting . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 Sprint review meeting . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 Sprint retrospective meeting . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6

Choosing suitable projects for agile . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 Why agile methods are better than traditional project managementfor a data warehouse project . . . . . . . . . . . . . . . . . . . 8 Agile data integration case study . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9

Agile Methodology for Data Warehouse and Data Integration Projects

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AbsTrACT
This case study explores the applicability of agile software development methods in thecontext of data warehouse and data Integration projects. The conclusion is that agile methods are indeed suitable if several modifications are made. Data warehouse projects differ from other software development projects in that a data warehouse is never really a completed project. Every phase of a data warehouse project has a start and an end, but the data warehouse will never go to a stable end...