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The Analytical Puzzle – Profitable Data Warehousing, Business Intelligence and Analytics

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Do you enjoy completing puzzles? Perhaps one of the most challenging (yet rewarding) puzzles is delivering a successful data warehouse. The Analytical Puzzle describes an unbiased, practical, and comprehensive approach to building a data warehouse which will lead to an increased level of business intelligence within your organization. New technologies continuously impact this approach and therefore this book explains how to leverage big data, cloud computing, data warehouse appliances, data mining, predictive analytics, data visualization and mobile devices.

Case studies and numerous examples reinforce concepts and after reading this book you
will be positioned to:

  • Plan and organize a successful data warehouse project
  • Sell the business intelligence effort using a sound business case
  • Determine which data to include in the data warehouse
  • Architect and design a high performance data warehouse
  • Structure the data warehouse for ease of use and navigation
  • Populate the data warehouse with data for informed decision making
  • Successfully use statistics, data mining, descriptive and predictive analytics
  • Save time and money by applying readily available tools
  • Identify your most profitable and least profitable customers
  • Present clear information to decision makers using data visualization for mobile devices
  • Avoid traps and pitfalls, so you can avoid problems and solve the Analytical Puzzle.

Chapter

What You Will Gain

CHAPTER 1:
Data Warehousing Perspectives
 
Learn the fundamntals and benefits of this exciting subject. This chapter introduces data warehousing, business intelligence and analytics.
CHAPTER 2:
Business Case and
Project
Management
 
Learn how to build the business case needed to sell your data warehousing project. Next, learn how to organize a data warehousing and business intelligence project. Make the winning moves and avoid the killer mistakes.
 
CHAPTER 3:
Business
Architecture and
Requirements
 
Learn how to elicit and organize business intelligence and data warehousing business requirements. The data warehouse requirements workshop is an effective and rapid way to elicit and document enterprise needs for data warehousing. Learn how to prepare for, conduct, and follow up on effective data warehouse requirements workshops.
 
CHAPTER 4:
Data Warehousing
Technical
Architecture
 
Learn to specify the big picture of the data warehousing system, including software components, infrastructure components, technology stack, and non-functional requirements. In addition, gain understanding of cloud based data warehousing and data warehouse appliances. 
CHAPTER 5:
Data Attributes
Learn about data attributes, the raw material of data warehousing and business intelligence. 
CHAPTER 6:
Data Modeling
Learn the basics of data modeling, which is data design through pictures. The language and symbols of data modeling are presented, along with step-bystep processes to make your data designs successful. Design patterns for each part of the data warehouse will help you to design the needed databases.
 
CHAPTER 7:
Dimensional
Modeling
Learn to model and design databases that directly support business intelligence. Welcome to the world of cubes, stars, and snowflakes, where slicing and dicing, pivoting, drilling down, and rolling up are the things to do. 
CHAPTER 8:
Data Governance
and Metadata
Management
Data governance is the overall management of data, including people, processes, and tools. Learn how to organize a successful data governance program. Learn how to manage metadata for your data warehousing and business intelligence project. 
CHAPTER 9:
Data Sources and
Data Quality
Management
 
Successful data warehousing and business intelligence depends on a supply of clean data. Learn how to identify and understand this important resource.
 
CHAPTER 10:
Database
Technology
Learn how to use database technology for your data warehousing project. In addition to relational database technology, you will learn about big data, data warehouse appliances, in memory databases, columnar databases and OnLine Analytical Processing(OLAP). 
CHAPTER 11:
Data Integration
Learn how to use data integration for your data warehousing project. Topics include: data integration architecture, data mapping, data cleansing, data transformation, and loading data. Selecting the right data movement tool is critical to the success of data warehousing projects. Learn how to determine tool requirements and then acquire the most appropriate tools. 
CHAPTER 12:
Business
Intelligence
Operations and
Tools
 
Learn to understand and use business intelligence (BI) operations terms, including slice, dice, drill down, roll up, and pivot. These are the main operations of exploratory BI. Gain an understanding of the types of BI tools that can help with your data warehousing project. Business intelligence tools are used to analyze and present data.
 
CHAPTER 13:
Number Crunching
Part 1: Statistics
 
Learn the basics of descriptive and predictive statistics. You will learn to calculate and understand mean, median, mode, variance and standard deviation. 
CHAPTER 14:
Number Crunching
Part 2: Data
Mining
Gain insights into your enterprise through data mining, which is the application of analytical methods to data. Learn to harness analytical methods such as data mining and statistics to anticipate the future. Learn how enterprises are making more effective decisions by using analytical methods such as: regression analysis, data mining, and statistics. 
CHAPTER 15:
Number Crunching
Part 3: Analytic
Application
 
Learn from an end-to-end example application. This example shows components and design patterns that compose a typical application. 
CHAPTER 16:
Presenting Data:
Scorecards and
Dashboards
Gain an understanding of the uses and benefits of scorecards. You will learn how to determine requirements for scorecards, select the best type of scorecard for your needs, and then how to design your scorecard. Gain expertise in the design and use of BI dashboards. Understand important dashboard terms and techniques. Apply methods to mobile technologies such as smart phones and tablets.
 
CHAPTER 17:
Business
Intelligence
Applications
Gain insight into applications of business intelligence that could of help to your organization. BI finds profitable uses in fields as diverse as risk management, finance, marketing, government, healthcare, science and sports. It is a great tool for fighting crime and detecting fraud as well. 
CHAPTER 18:
Customer Analytics
Learn how to understand your customers better. Identify the profiles of your most profitable and least profitable customers. 
CHAPTER 19:
Testing, Rolling
Out, and
Sustaining the
Data Warehouse
 
Successful business intelligence efforts require that business users must have faith that the system is producing correct answers. Learn how to put together the testing approach that ensures a trusted system. Learn to create and execute a plan for rolling out your data warehouse.
 
APPENDIX A:
Glossary
Learn to talk the talk. This glossary provides definitions and explanations of the critical data warehousing and business intelligence terms that you must know.
 
APPENDIX B:
Bibliography
Learn to learn. The bibliography points you to further learning opportunities in the field of data warehousing and business intelligence.
 
APPENDIX C:
References
Learn the source of this book’s quotes and case studies. The references appendix directs you to supporting information for additional learning.