Data Warehousing and Business Intelligence at the Data Management Center 

Data Warehousing Tutorial

Learn Data Warehousing and Business Intelligence.
Jump start your data warehousing efforts.
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Welcome to Data Warehousing and Business Intelligence Tutorials including: OLAP, BI, Architecture, Data Marts, and more.

David Haertzen David Haertzen, Principal Enterprise Architect

Times are changing in the field of data warehousing and business intelligence, so I wrote this tutorial and accompanying book to provide a fresh perspective on the field.

Upon finishing this tutorial, you will understand what data warehousing, business intelligence, and analytics are. You will be familiar with the goals of and components that make up data warehousing, business intelligence, and analytics. In addition, approaches used by data warehousing professionals will become clear. Examples in the tutorial will enable you to be ready to work and manage others in the field of data warehousing.

The book, The Analytical Puzzle: Profitable Data Warehousing, Business Intelligence and Analytics provides even more details - plus over 20 helpful templates to accelerate your data warehousing and analytics projects.

 

You will better understand: 

  • How to get the right people involved in the project
  • How to determine data warehouse business requirements
  • How to choose between a data warehouse and a data mart
  • How to load the data warehouse
  • How to choose data going into the data warehouse
  • How to achieve the benefits of business intelligence
  • How to manage the ongoing data warehouse
  • How to define a data warehousing architecture
  • How to create data models for data warehouses and data marts
  • How to avoid traps and pitfalls, so you can avoid problems and succeed
  • How to present information to users of the data warehouse and business intelligence system.

 


 Data Warehousing and Business Intelligence Introduction

This tutorial introduces data warehousing and business intelligence. Learn the fundamentals and benefits of this exciting subject.
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Project Management for Data Warehousing

Learn how to organize a data warehousing and business intelligence project. Make the winning moves and avoid the killer mistakes.
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Data Warehousing and Business Intelligence Methodology

Learn the steps of successful data warehousing and business intelligence efforts. These proven steps can put your time on the path to success.
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Data Warehousing Business Requirements

Learn how to gather and organize business intelligence and data warehousing business requirements.
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Data Modeling for Data Warehouse

Data models are key to successful for data warehouses and data marts. Design patterns for each part of the data warehouse will help you to design needed databases.
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Metadata for Data Warehousing and Business Intelligence

Metadata is often called "data about data". Learn how to manage metadata for your data warehousing and business intelligence project.
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ETL : Extract, Transform, Load

Learn how to use ETL for your data warehousing project. Topics include: ETL architecture, data mapping, data cleansing, data transformation and loading data.
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Data Warehousing Databases

Which database software and features should you use for you data warehousing project? Learn how to use database technology for your data warehousing project.
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OLAP / MOLAP / ROLAP

OLAP (OnLine Analytical Processing) is a key technology for data warehousing and business intelligence. Learn how to strengths and weaknesses of OLAP forms: MOLAP, ROLAP and HOLAP.
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BI / Business Intelligence

Business intelligence tools are used to analyze and present data. Gain an understanding of types of business intelligence (BI) that can help with your data warehousing project.
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Data Warehousing Rollout

The rollout is the project phase when the data warehousing / business intelligence system is made available to its users. Follow these steps to increase your chances of success.
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Sustaining BI and Data Warehousing

A sustainable program will keep your BI and Data Warehousing efforts moving in the right direction.
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The Analytical Puzzle: Profitable Data Warehousing, Business Intelligence and Analytics
By David Haertzen
The Analytical Puzzle