The Data Warehouse Mentor: Practical Data Warehouse and Business Intelligence Insights / Edition 1

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Overview

Develop a custom, agile data warehousing and business intelligence architecture

Empower your users and drive better decision making across your enterprise with detailed instructions and best practices from an expert developer and trainer. The Data Warehouse Mentor: Practical Data Warehouse and Business Intelligence Insights shows how to plan, design, construct, and administer an integrated end-to-end DW/BI solution. Learn how to choose appropriate components, build an enterprise data model, configure data marts and data warehouses, establish data flow, and mitigate risk. Change management, data governance, and security are also covered in this comprehensive guide.

  • Understand the components of BI and data warehouse systems
  • Establish project goals and implement an effective deployment plan
  • Build accurate logical and physical enterprise data models
  • Gain insight into your company's transactions with data mining
  • Input, cleanse, and normalize data using ETL (Extract, Transform, and Load) techniques
  • Use structured input files to define data requirements
  • Employ top-down, bottom-up, and hybrid design methodologies
  • Handle security and optimize performance using data governance tools

Robert Laberge is the founder of several Internet ventures and a principle consultant for the IBM Industry Models and Assets Lab, which has a focus on data warehousing and business intelligence solutions.

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Product Details

  • ISBN-13: 9780071745321
  • Publisher: McGraw-Hill Professional Publishing
  • Publication date: 5/12/2011
  • Edition number: 1
  • Pages: 416
  • Sales rank: 780,798
  • Product dimensions: 7.30 (w) x 9.10 (h) x 1.00 (d)

Meet the Author

Robert Laberge is a lead principle consultant for the IBM Industry Models and Assets Lab in Dublin which focuses on data warehousing and business intelligence solutions. He has helped more than 50 large organizations in 20 countries by mentoring, training, and demonstrating data warehouse and business intelligence solutions, including Target, Qwest, ING, Mayo Clinic, Canadian Tire, Shoppers Drug Mart, BMW, Korea Telecom, Scotiabank, Capital One, Reliance Infocomm, and Tata Group. Robert has a Masters of Business Administration from the University of Durham (UK) and has nearly 30 years of experience in IT.

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Table of Contents

Part I: Preparation
Chapter 1: Data Warehouse and Business Intelligence Overview
Chapter 2: Data in the Organization
Chapter 3: Reasons for Building
Chapter 4: Business Intelligence and Data Warehouse Strategy
Chapter 5: Project Resources: Roles and Insights
Chapter 6: Write-It-Up Overview
Part II: Components
Chapter 7: Business Intelligence: Data Marts and Usage
Chapter 8: Enterprise Data Models
Chapter 9: Data Warehouse Architecture: Components
Chapter 10: ETL and Data Quality
Chapter 11: Project Planning and Methodology
Part III: Let's Build
Chapter 12: Working Scenarios
Chapter 13: Data Governance
Chapter 14: Post-Project Review
Index

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