book

Data Warehousing For Dummies®, 2nd Edition

Name: Data Warehousing For Dummies®, 2nd Edition
Author: Thomas C. Hammergren
ISBN: 9780470407479

by Thomas C. Hammergren

March 2009

Beginner to intermediate

384 pages

8h 40m

English

For Dummies

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Copyright
About The Author
Author's Acknowledgments
Publisher's Acknowledgments
Introduction
Why I Wrote This BookHow to Use This BookPart I: The Data Warehouse: Home for Your Data AssetsPart II: Data Warehousing TechnologyPart III: Business Intelligence and Data WarehousingPart IV: Data Warehousing Projects: How to Do Them RightPart V: Data Warehousing: The Big PicturePart VI: Data Warehousing in the Not-Too-Distant FuturePart VII: The Part of TensIcons Used in This BookAbout the Product References in This Book
I. The Data Warehouse: Home for Your Data Assets
1. What's in a Data Warehouse?
1.1. The Data Warehouse: A Place for Your Data Assets1.1.1. Classifying data: What is a data asset?1.1.2. Manufacturing data assets1.2. Data Warehousing: A Working Definition1.2.1. Today's data warehousing defined1.2.2. A broader, forward looking definition1.3. A Brief History of Data Warehousing1.3.1. Before our time — the foundation1.3.2. The 1970s — the preparation1.3.3. The 1980s — the birth1.3.4. The 1990s — the adolescent1.3.5. The 2000s — the adult1.4. Is a Bigger Data Warehouse a Better Data Warehouse?1.5. Realizing That a Data Warehouse (Usually) Has a Historical Perspective1.6. It's Data Warehouse, Not Data Dump
2. What Should You Expect from Your Data Warehouse?
2.1. Using the Data Warehouse to Make Better Business Decisions2.2. Finding Data at Your Fingertips2.3. Facilitating Communications with Data Warehousing2.3.1. IT-to-business organization communications2.3.2. Communications across business organizations2.4. Facilitating Business Change with Data Warehousing
3. Have It Your Way: The Structure of a Data Warehouse
3.1. Ensuring That Your Implementations Are Unique3.2. Classifying the Data Warehouse3.2.1. The data warehouse lite3.2.1.1. Subject areas and data content3.2.1.2. Data sources3.2.1.3. Business intelligence tools3.2.1.4. Database3.2.1.5. Data extraction, movement, and loading3.2.1.6. Architecture3.2.2. The data warehouse deluxe3.2.2.1. Subject areas and data content3.2.2.2. Data sources3.2.2.3. Business intelligence tools3.2.2.4. Database3.2.2.5. Data extraction, movement, and loading3.2.2.6. Architecture3.2.3. The data warehouse supreme3.2.3.1. Subject areas and data content3.2.3.2. Data sources3.2.3.3. Business intelligence tools3.2.3.4. Database3.2.3.5. Data extraction, movement, and loading3.2.3.6. Architecture3.3. To Centralize or Distribute, That Is the Question
4. Data Marts: Your Retail Data Outlet
4.1. Architectural Approaches to Data Marts4.1.1. Data marts sourced by a data warehouse4.1.2. Top-down, quick-strike data marts4.1.3. Bottom-up, integration-oriented data marts4.2. What to Put in a Data Mart4.2.1. Geography-bounded data4.2.2. Organization-bounded data4.2.3. Function-bounded data4.2.4. Market-bounded data4.2.5. Answers to specific business questions4.2.6. Anything!4.3. Data mart or data warehouse?4.4. Implementing a Data Mart — Quickly

II. Data Warehousing Technology
5. Relational Databases and Data Warehousing
5.1. The Old Way of Thinking5.1.1. A technology-based discussion: The roots of relational database technology5.1.2. The OLAP-only fallacy5.2. The New Way of Thinking5.2.1. Fine-tuning databases for data warehousing5.2.2. Optimizing data access5.2.3. Avoiding scanning unnecessary data5.2.4. Handling large data volume5.3. Designing Your Relational Database for Data Warehouse Usage5.3.1. Looking at why traditional relational design techniques don't work well5.3.1.1. Explaining normalization in plain language (or trying to)5.3.1.2. The side effect of normalization5.3.2. Exploring new ways to design a relational-based data warehouse5.4. Relational Products and Data Warehousing5.4.1. IBM Data Management family5.4.2. Microsoft SQL Server5.4.3. Oracle
6. Specialty Databases and Data Warehousing
6.1. Multidimensional Databases6.1.1. The idea behind multidimensional databases6.1.1.1. The basics6.1.1.2. Is there a limit to the number of dimensions?6.1.1.3. How should I choose the levels in a hierarchy?6.1.1.4. Physical database structures in an MDDB6.1.2. Are multidimensional databases still worth looking at?6.2. Horizontal versus Vertical Data Storage Management6.3. Data Warehouse Appliances6.4. Data Warehousing Specialty Database Products6.4.1. Cognos (An IBM company)6.4.2. Microsoft6.4.3. Oracle6.4.4. Sybase IQ6.4.5. Vertica
7. Stuck in the Middle with You: Data Warehousing Middleware
7.1. What Is Middleware?7.2. Middleware for Data Warehousing7.2.1. The services7.2.2. Should you use tools or custom code?7.3. What Each Middleware Service Does for You7.3.1. Data selection and extractions7.3.2. Data quality assurance, part I7.3.3. Data movement, part I7.3.4. Data mapping and transformation7.3.5. Data quality assurance, part II7.3.6. Data movement, part II7.3.7. Data loading7.4. Specialty Middleware Services7.4.1. Replication services for data warehousing7.4.2. Enterprise Information Integration services7.4.2.1. EII architecture7.4.2.2. Additional EII services7.4.2.3. Facing the EII infrastructure challenge7.5. Vendors with Middleware Products for Data Warehousing7.5.1. Composite Software7.5.2. IBM7.5.3. Informatica7.5.4. Ipedo7.5.5. Microsoft7.5.6. Oracle7.5.7. Sybase (Avaki)
III. Business Intelligence and Data Warehousing
8. An Intelligent Look at Business Intelligence
8.1. The Main Categories of Business Intelligence8.1.1. Querying and reporting8.1.2. Business analysis (OLAP)8.1.3. Data mining8.1.4. Dashboards and scorecards8.2. Other Types of Business Intelligence8.2.1. Statistical processing8.2.2. Geographical information systems8.2.3. Mash-ups8.2.4. Business intelligence applications8.3. Business Intelligence Architecture and Data Warehousing
9. Simple Database Querying and Reporting
9.1. What Functionality Does a Querying and Reporting Tool Provide?9.1.1. The role of SQL9.1.2. Technical query tools9.1.3. User query tools9.1.4. Reporting tools9.1.5. The idea of managed queries and reports9.2. Is This All You Need?9.3. Designing a Relational Database for Querying and Reporting Support9.4. Vendors with Querying and Reporting Products for Data Warehousing9.4.1. Business Objects (SAP)9.4.2. Cognos (IBM)9.4.3. Information Builders9.4.4. Microsoft9.4.5. Oracle
10. Business Analysis (OLAP)
10.1. What Is Business Analysis?10.2. The OLAP Acronym Parade10.2.1. Business analysis (Visualization)10.2.2. OLAP middleware10.2.3. OLAP databases10.3. First, an Editorial10.4. Business Analysis (OLAP) Features: An Overview10.4.1. Drill-down10.4.2. Drill-up10.4.3. Drill-across10.4.4. Drill-through10.4.5. Pivoting10.4.6. Trending10.4.7. Nesting10.4.8. Visualizing10.5. Data Warehousing Business Analysis Vendors10.5.1. IBM10.5.2. MicroStrategy10.5.3. Oracle10.5.4. Pentaho10.5.5. SAP10.5.6. SAS
11. Data Mining: Hi-Ho, Hi-Ho, It's Off to Mine We Go
11.1. Data Mining in Specific Business Missions11.2. Data Mining and Artificial Intelligence11.3. Data Mining and Statistics11.4. Some Vendors with Data Mining Products11.4.1. Microsoft11.4.2. SAS11.4.3. SPSS
12. Dashboards and Scorecards
12.1. Dashboard and Scorecard Principles12.1.1. Dashboards12.1.2. Scorecards12.2. The Relationship between Dashboards, Scorecards, and the Other Parts of Business Intelligence12.3. EIS and Key Indicators12.4. The Briefing Book12.5. The Portal Command Center12.6. Who Produces EIS Products
IV. Data Warehousing Projects: How to Do Them Right
13. Data Warehousing and Other IT Projects: The Same but Different
13.1. Why a Data Warehousing Project Is (Almost) Like Any Other Development Project13.2. How to Apply Your Company's Best Development Practices to Your Project13.3. How to Handle the Uniqueness of Data Warehousing13.4. Why Your Data Warehousing Project Must Have Top-Level Buy-In13.5. How Do I Conduct a Large, Enterprise-Scale Data Warehousing Initiative?13.5.1. Top-down13.5.2. Bottom-up13.5.3. Mixed-mode
14. Building a Winning Data Warehousing Project Team
14.1. Don't Make This Mistake!14.2. The Roles You Have to Fill on Your Project14.2.1. Project manager14.2.2. Technical leader14.2.3. Chief architect14.2.4. Business requirements analyst14.2.5. Data modeler and conceptual/logical database designer14.2.6. Database administrator and physical database designer14.2.7. Front-end tools specialist and developer14.2.8. Middleware specialist14.2.9. Quality assurance (QA) specialist14.2.10. Source data analyst14.2.11. User community interaction manager14.2.12. Technical executive sponsor14.2.13. User community executive sponsor14.3. And Now, the People14.4. Organizational Operating Model
15. You Need What? When? — Capturing Requirements
15.1. Choosing between Being Business or Technically Driven15.2. Technically-Driven Data Warehousing15.2.1. Subject area15.2.2. Enterprise data modeling15.3. Business-Driven Business Intelligence15.3.1. Starting with business questions15.3.2. Accessing the value of the information15.3.3. Defining key business objects15.3.4. Building a business model15.3.5. Prototyping and iterating with the users15.3.6. Signing off on scope
16. Analyzing Data Sources
16.1. Begin with Source Data Structures, but Don't Stop There16.2. Identify What Data You Need to Analyze16.3. Line Up the Help You'll Need16.4. Techniques for Analyzing Data Sources and Their Content16.5. Analyze What's Not There: Data Gap Analysis16.6. Determine Mapping and Transformation Logic
17. Delivering the Goods
17.1. Exploring Architecture Principles17.1.1. What's an architecture?17.1.2. What's an adaptable architecture?17.2. Understanding Data Warehousing Architectural Keys17.2.1. People and their roles17.2.2. Consistent delivery process17.2.3. Standard delivery platform17.3. Assessing Your Data Warehouse Architecture17.3.1. What are you building?17.3.2. How are you building it?17.3.3. Is the delivery automated?17.4. Architecting through Abstraction
18. User Testing, Feedback, and Acceptance
18.1. Getting Users Involved Early in Data Warehousing18.2. Using Real Business Situations18.3. Ensuring That Users Provide Necessary Feedback18.4. After the Scope: Involving Users during Design and Development18.5. Understanding What Determines User Acceptance
V. Data Warehousing: The Big Picture
19. The Information Value Chain: Connecting Internal and External Data
19.1. Identifying Data You Need from Other People19.2. Recognizing Why External Data Is Important19.3. Viewing External Data from a User's Perspective19.4. Determining What External Data You Really Need19.5. Ensuring the Quality of Incoming External Data19.6. Filtering and Reorganizing Data after It Arrives19.7. Restocking Your External Data19.8. Acquiring External Data19.8.1. Finding external information19.8.2. Gathering general information19.8.3. Cruising the Internet19.9. Maintaining Control over External Data19.9.1. Staying on top of changes19.9.2. Knowing what to do with historical external data19.9.3. Determining when new external data sources are available19.9.4. Switching from one external data provider to another
20. Data Warehousing Driving Quality and Integration
20.1. The Infrastructure Challenge20.2. Data Warehouse Data Stores20.2.1. Source data feeds20.2.2. Operational data store (ODS)20.2.2.1. The ODS defined20.2.2.2. An ODS example20.2.2.3. ODS feedback loops20.2.3. Master data management (MDM)20.2.4. Service-oriented architecture (SOA)20.3. Dealing with Conflict: Special Challenges to Your Data Warehousing Environment
21. The View from the Executive Boardroom
21.1. What Does Top Management Need to Know?21.1.1. Tell them this21.1.2. Keep selling the data warehousing project21.2. Data Warehousing and the Business-Trends Bandwagon21.3. Data Warehousing in a Cross-Company Setting21.4. Connecting the Enterprise
22. Existing Sort-of Data Warehouses: Upgrade or Replace?
22.1. The Data Haves and Have-Nots22.1.1. The first step: Cataloguing the extract files, who uses them, and why22.1.2. And then, the review22.2. Decisions, Decisions22.2.1. Choice 1: Get rid of it22.2.2. Choice 2: Replace it22.2.3. Choice 3: Retain it22.3. Caution: Migration Isn't Development — It's Much More Difficult22.4. Beware: Don't Take Away Valued Functionality
23. Surviving in the Computer Industry (and Handling Vendors)
23.1. How to Be a Smart Shopper at Data Warehousing Conferences and Trade Shows23.1.1. Do your homework first23.1.2. Ask a lot of questions23.1.3. Be skeptical23.1.4. Don't get rushed into a purchase23.2. Dealing with Data Warehousing Product Vendors23.2.1. Check out the product and the company before you begin discussions23.2.2. Take the lead during the meeting23.2.3. Be skeptical — again23.2.4. Be a cautious buyer23.3. A Look Ahead: Data Warehousing, Mainstream Technologies, and Vendors
24. Working with Data Warehousing Consultants
24.1. Do You Really Need Consultants to Help Build a Data Warehouse?24.2. Watch Out, Though!24.3. A Final Word about Data Warehousing Consultants
VI. Data Warehousing in the Not-too-Distant Future
25. Expanding Your Data Warehouse with Unstructured Data
25.1. Traditional Data Warehousing Means Analyzing Traditional Data Types25.2. It's a Multimedia World, After All. . . .25.3. How Does Business Intelligence Work with Unstructured Data?25.4. An Alternative Path: From Unstructured Information to Structured Data
26. Agreeing to Disagree about Semantics
26.1. Defining Semantics26.2. Emergence of the Semantic Web?26.3. Preparing for Semantic Data Warehousing26.4. Starting Out on Your Semantic Journey26.4.1. Business intelligence semantic layer management26.4.2. Business rules management
27. Collaborative Business Intelligence
27.1. Future Business Intelligence Support Model27.1.1. Knowledge retention27.1.2. Knowledge discovery27.1.3. Knowledge proliferation27.2. Leveraging Examples from Highly Successful Collaboration Solutions27.2.1. Rate a report27.2.2. Report relationships27.2.3. Find a report27.2.4. Find the meaning27.2.5. Shared interests — shared information27.2.6. Visualization27.3. The Vision of Collaborative Business Intelligence
VII. The Part of Tens
28. Ten Questions to Consider When You're Selecting User Tools
28.1. Do I Want a Smorgasbord or a Sit-Down Restaurant?28.2. Can a User Stop a Runaway Query or Report?28.3. How Does Performance Differ with Varying Amounts of Data?28.4. Can Users Access Different Databases?28.5. Can Data Definitions Be Easily Changed?28.6. How Does the Tool Deploy?28.7. How Does Performance Change if You Have a Large Number of Users?28.8. What Online Help and Assistance Is Available, and How Good Is It?28.9. Does the Tool Support Interfaces to Other Products?28.10. What Happens When You Pull the Plug?
29. Ten Secrets to Managing Your Project Successfully
29.1. Tell It Like It Is29.2. Put the Right People in the Right Roles29.3. Be a Tough but Fair Negotiator29.4. Deal Carefully with Product Vendors29.5. Watch the Project Plan29.6. Don't Micromanage29.7. Use a Project Wiki29.8. Don't Overlook the Effect of Organizational Culture29.9. Don't Forget about Deployment and Operations29.10. Take a Breather Occasionally
30. Ten Sources of Up-to-Date Information about Data Warehousing
30.1. The Data Warehousing Institute30.2. The Data Warehousing Information Center30.3. The OLAP Report30.4. Intelligent Enterprise30.5. b-eye Business Intelligence Network30.6. Wikipedia30.7. DMReview.com30.8. BusinessIntelligence.com30.9. Industry Analysts' Web Sites30.10. Product Vendors' Web Sites
31. Ten Mandatory Skills for a Data Warehousing Consultant
31.1. Broad Vision31.2. Deep Technical Expertise in One or Two Areas31.3. Communications Skills31.4. The Ability to Analyze Data Sources31.5. The Ability to Distinguish between Requirements and Wishes31.6. Conflict-Resolution Skills31.7. An Early-Warning System31.8. General Systems and Application Development Knowledge31.9. The Know-How to Find Up-to-Date Information31.10. A Hype-Free Vocabulary
32. Ten Signs of a Data Warehousing Project in Trouble
32.1. The Project's Scope Phase Ends with No General Consensus32.2. The Mission Statement Gets Questioned after the Scope Phase Ends32.3. Tools Are Selected without Adequate Research32.4. People Get Pulled from Your Team for "Just a Few Days"32.5. You're Overruled When You Attempt to Handle Scope Creep32.6. Your Executive Sponsor Leaves the Company32.7. You Overhear, "This Will Never Work, but I'm Not Saying Anything"32.8. You Find a Major "Uh-Oh" in One of the Products You're Using32.9. The IT Organization Responsible for Supporting the Project Pulls Its Support32.10. Resignations Begin
33. Ten Signs of a Successful Data Warehousing Project
33.1. The Executive Sponsor Says, "This Thing Works — It Really Works!"33.2. You Receive a Flood of Suggested Enhancements and Additional Capabilities33.3. User Group Meetings Are Almost Full33.4. The User Base Keeps Growing and Growing and Growing33.5. The Executive Sponsor Cheerfully Volunteers Your Company as a Reference Site33.6. The Company CEO Asks, "How Can I Get One of Those Things?"33.7. The Response to Your Next Funding Request Is, "Whatever You Need — It's Yours."33.8. You Get Promoted — and So Do Some of Your Team Members33.9. You Achieve Celebrity Status in the Company33.10. You Get Your Picture on the Cover of the Rolling Stone
34. Ten Subject Areas to Cover with Product Vendors
34.1. Product's Chief Architect34.2. Development Team34.3. Customer Feedback34.4. Employee Retention34.5. Marketplace34.6. Product Uniqueness34.7. Clients34.8. The Future34.9. Internet and Internet Integration Approach34.10. Integrity

Content preview from Data Warehousing For Dummies®, 2nd Edition

Part IV. Data Warehousing Projects: How to Do Them Right

In this part . . .

A data warehousing project is just like any other application development project. Or, to be more blunt, you can mess up a perfectly good data warehouse effort in a lot of ways: poor project management, putting the wrong people on the development team — you get the idea.

If you want to find out how to do a data warehouse project the right way, this part of the book is for you! I uncover what aspects of developing data warehouses are the same as traditional applications and what few subtleties can alter your approach to building a data warehouse from traditional applications.

Become an O’Reilly member and get unlimited access to this title plus top books and audiobooks from O’Reilly and nearly 200 top publishers, thousands of courses curated by job role, 150+ live events each month,
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Data Warehousing For Dummies®, 2nd Edition

by Thomas C. Hammergren

Part IV. Data Warehousing Projects: How to Do Them Right

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