The Kimball Group Reader: Relentlessly Practical Tools for Data Warehousing and Business Intelligence

by Ralph Kimball (et al.); Margy Ross; Contributions by: Warren Thornthwaite (Menlo Park, CA); Contributions by: Joy Mundy (Menlo Park, CA); Contributions by: Bob Becker

• ISBN13: 9780470630532
• ISBN10: 0470630531
• Format: eBook
• Copyright: 2010-02-01
• Publisher: Wiley

Summary

An unparalleled collection of recommended guidelines for data warehousing and business intelligence pioneered by Ralph Kimball and his team of colleagues from the Kimball Group. Recognized and respected throughout the world as the most influential leaders in the data warehousing industry, Ralph Kimball and the Kimball Group have written articles covering more than 250 topics that define the field of data warehousing. For the first time, the Kimball Group's incomparable advice, design tips, and best practices have been gathered in this remarkable collection of articles, which spans a decade of data warehousing innovation. Each group of articles is introduced with original commentaries that explain their role in the overall lifecycle methodology developed by the Kimball Group. These practical, hands-on articles are fully updated to reflect current practices and terminology and cover the complete lifecycle-including project planning, requirements gathering, dimensional modeling, ETL, and business intelligence and analytics. This easily referenced collection is nothing less than vital if you are involved with data warehousing or business intelligence in any capacity.

Table of Contents

Introduction

The Reader at a Glance

Setting Up for Success

Resist the Urge to Start Coding

Set Your Boundaries

Data Wrangling

Myth Busters

Dividing the World

Essential Steps for the Integrated Enterprise Data Warehouse

Drill Down to Ask Why

Slowly Changing Dimensions

Judge Your BI Tool through Your Dimensions

Fact Tables

Exploit Your Fact Tables

Before You Dive In

Historical Perspective

The Database Market Splits

Bringing Up Supermarts

Brave New Requirements for Data Warehousing

Coping with the Brave New Requirements

Stirring Things Up

Design Constraints and Unavoidable Realities

Two Powerful Ideas

Data Warehouse Dining Experience

Project/Program Planning

Professional Responsibilities

Professional Boundaries

An Engineer's View

Beware the Objection Removers

What Does the Central Team Do?

Avoid DW/BI Isolation

Implementation Analysis Paralysis

Habits of Effective Sponsors

TCO Starts with the End User

Better Business Skills for BI and Data Warehouse Professionals

Kimball Lifecycle in a Nutshell

Off the Bench

The Anti-Architect

Think Critically When Applying Best Practices

Eight Guidelines for Low Risk Enterprise Data Warehousing

Relating to Agile Methodologies

Is Agile Enterprise Data Warehousing an Oxymoron?

Requirements Definition

Gathering Requirements

Alan Alda's Interviewing Tips for Uncovering

More Business Requirements Gathering Dos and Don'ts

Overcoming Obstacles When Gathering Business Requirements

Surprising Value of Data Profiling

Focus on Business Processes, Not Business Departments!

Identifying Business Processes

Business Process Decoder Ring

Relationship between Strategic Business Initiatives and Business Processes

The Bottom-Up Misnomer

Data Architecture

Making the Case for Dimensional Modeling

Is ER Modeling Hazardous to DSS?

A Dimensional Modeling Manifesto

There Are No Guarantees

Divide and Conquer

The Matrix

The Matrix: Revisited

Drill Down into a Detailed Bus Matrix

Integration Instead of Centralization

Integration for Real People

Data Stewardship 101: The First Step to Quality and Consistency

To Be or Not To Be Centralized

Differences of Opinion

Don't Support Business Intelligence with a Normalized EDW

Dimensional Modeling Fundamentals

Basics of Dimensional Modeling

Fact Tables and Dimension Tables

Drilling Down, Up, and Across

The Soul of the Data Warehouse, Part One: Drilling Down

The Soul of the Data Warehouse, Part Two: Drilling Across

The Soul of the Data Warehouse, Part Three: Handling Time

Graceful Modifications to Existing Fact and Dimension Tables

Kimball's Ten Essential Rules of Dimensional Modeling

What Not to Do

Dangerous Preconceptions

Fables and Facts

Dimensional Modeling Tasks and Responsibilities

Design Activities

Letting the Users Sleep

Staffing the Dimensional Modeling Team

Practical Steps for Designing a Dimensional Model

The Naming Game

When Is the Dimensional Design Done?

Fistful of Flaws

Rating Your Dimensional Data Warehouse

Fact Table Core Concepts

Granularity

Declaring the Grain

Keep to the Grain in Dimensional Modeling

Warning: Summary Data May Be Hazardous to Your Health

No Detail Too Small

Fundamental Grains

Modeling a Pipeline with an Accumulating Snapshot

Combining Periodic and Accumulating Snapshots

Modeling Time Spans

A Rolling Prediction of the Future, Now and in the Past

Factless Fact Tables

Factless Fact Tables? Sound Like Jumbo Shrimp?

What Didn't Happen

Managing Your Parents

Patterns to Avoid When Modeling Header/Line Item Transactions

Fact Table Surrogate Keys

Reader Suggestions on Fact Table Surrogate Keys

Another Look at Degenerate Dimensions

Creating a Reference Dimension for Infrequently Accessed Degenerates

Put Your Fact Tables on a Diet

Keeping Text Out of the Fact Table

Dealing with Nulls in a Dimensional Model

Modeling Data as Both a Fact and Dimension Attribute

When a Fact Table Can Be Used as a Dimension Table

Sparse Facts and Facts with Short Lifetimes

Pivoting the Fact Table with a Fact Dimension

Dimension Table Core Concepts

Dimension Table Keys

Surrogate Keys

Keep Your Keys Simple

It's Time for Time

Surrogate Keys for the Time Dimension

Latest Thinking on Time Dimension Tables

Smart Date Keys to Partition Fact Tables

Handling All the Dates

Miscellaneous Dimension Patterns

Data Warehouse Role Models

Mystery Dimensions

De-Clutter with Junk Dimensions

Showing the Correlation Between Dimensions

Causal (Not Casual) Dimensions

Resist Abstract Generic Dimensions

Hot-Swappable Dimensions

Accurate Counting with a Dimensional Supplement

Perfectly Partitioning History with Type 2 SCD

Many Alternate Realities

Monster Dimensions

When a Slowly Changing Dimension Speeds Up

When Do Dimensions Become Dangerous?

Slowly Changing Dimensions Are Not Always as Easy as 1, 2, and 3

Dimension Row Change Reason Attributes

More Dimension Patterns and Case Studies

Snowflakes, Outriggers, and Bridges

Snowflakes, Outriggers, and Bridges

A Trio of Interesting Snowflakes

Help for Dimensional Modeling

Managing Bridge Tables

The Keyword Dimension

Maintaining Dimension Hierarchies

Help for Hierarchies

Five Alternatives for Better Employee Dimensional Modeling

Alternate Hierarchies

Dimension Embellishments

Wrangling Behavior Tags

Three Ways to Capture Customer Satisfaction

Think Globally, Act Locally

Warehousing without Borders

Spatially Enabling Your Data Warehouse

Multinational Dimensional Data Warehouse Considerations

An Insurance Data Warehouse Case Study

Traveling through Databases

Human Resources Dimensional Models

Not So Fast

The Budgeting Chain

Compliance-Enabled Data Warehouses

Clicking with Your Customer

The Special Dimensions of the Clickstream

Fact Tables for Text Document Searching

Enabling Market Basket Analysis

Back Room ETL and Data Quality

Planning the ETL System

Surrounding the ETL Requirements

The 34 Subsystems of ETL

Doing the Work at Extract Time

Is Data Staging Relational?

Staging Areas and ETL Tools

Should You Use an ETL Tool?

Document the ETL System

Measure Twice, Cut Once

Brace for Incoming

Building a Change Data Capture System

Data Quality Considerations

Dealing with Dirty Data

An Architecture for Data Quality

Indicators of Quality

Is Your Data Correct?

Eight Recommendations for International Data Quality

Using Regular Expressions for Data Cleaning

Pipelining Your Surrogates

Replicating Dimensions Correctly

Identify Dimension Changes Using Cyclic Redundancy Checksums

Maintaining Back Pointers to Operational Sources

Creating Historical Dimension Rows

Backward in Time

Early-Arriving Facts

Slowly Changing Entities

Creating, Using, and Maintaining Junk Dimensions

Using the SQL MERGE for Slowly Changing Dimensions

Being Offline as Little as Possible

Working in Web Time

Real-Time Partitions

The Real-Time Triage

Technical Architecture Considerations

Overall Technical/System Architecture

Can the Data Warehouse Benefit from SOA?

Picking the Right Approach to MDM

Building Custom Tools for the DW/BI System

Welcoming the Packaged App

ERP Vendors: Bring Down Those Walls

Building a Foundation for Smart Applications

RFID Tags and Smart Dust

The Aggregate Navigator

Aggregate Navigation with (Almost) No Metadata

Relating to OLAP

Dimensional Relational versus OLAP: The Final Deployment Conundrum

Dimensional Modeling for Microsoft Analysis Services

Architecting Your Data for Microsoft SQL Server 2005

Microsoft SQL Server Comes of Age for Data Warehousing

The Second Revolution of User Interfaces

Designing the User Interface

Meta Meta Data Data

Creating the Metadata Strategy

Watching the Watchers

Catastrophic Failure

Digital Preservation

Creating the Advantages of a 64-Bit Server

Server Configuration Considerations

Adjust Your Thinking for SANs

Front Room Business Intelligence Applications

Delivering Value with Business Intelligence

The Promise of Decision Support

Beyond Paving the Cow Paths

Big Shifts Happening in BI

Behavior: The Next Marquee Application

Implementing the Business Intelligence Layer

Think Like a Software Development Manager

Standard Reports: Basics for Business Users

Building and Delivering BI Reports

The BI Portal

Dashboards Done Right

Don't Be Overly Reliant on Your Data Access Tool's Metadata

Mining Data to Uncover Relationships

Digging into Data Mining

Preparing for Data Mining

The Perfect Handoff

Get Started with Data Mining Now

Dealing with SQL

Simple Drill Across in SQL

The Problem with Comparisons

SQL Roadblocks and Pitfalls

Features for Query Tools

Turbocharge Your Query Tools

Smarter Data Warehouses

Maintenance and Growth Considerations

Deploying Successfully

Don't Forget the Owner's Manual

Let's Improve Our Operating Procedures

Marketing the DW/BI System

Coping with Growing Pains

Sustaining for Ongoing Impact

Data Warehouse Checkups

Boosting Business Acceptance

Educate Management to Sustain DW/BI Success

Getting Your Data Warehouse Back on Track

Upgrading Your BI Architecture

Four Fixes for Legacy Data Warehouses

A Data Warehousing Fitness Program for Lean Times

Index of Articles

Index

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