Data Modeling Made Simple
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Home > Computing and Information Technology > Databases > Data Modeling Made Simple: A Practical Guide for Business & IT Professionals: 2nd Edition
Data Modeling Made Simple: A Practical Guide for Business & IT Professionals: 2nd Edition

Data Modeling Made Simple: A Practical Guide for Business & IT Professionals: 2nd Edition


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About the Book

Read today's business headlines and you will see that many issues stem from people not having the right data at the right time. Data issues don't always make the front page, yet they exist within every organisation. We need to improve how we manage data -- and the most valuable tool for explaining, vaildating and managing data is a data model. This book provides the business or IT professional with a practical working knowledge of data modelling concepts and best practices. This book is written in a conversational style that encourages you to read it from start to finish and master these ten objectives: Know when a data model is needed and which type of data model is most effective for each situation; Read a data model of any size and complexity with the same confidence as reading a book; Build a fully normalised relational data model, as well as an easily navigatable dimensional model; Apply techniques to turn a logical data model into an efficient physical design; Leverage several templates to make requirements gathering more efficient and accurate; Explain all ten categories of the Data Model Scorecard(R); Learn strategies to improve your working relationships with others; Appreciate the impact unstructured data has, and will have, on our data modelling deliverables; Learn basic UML concepts; Put data modelling in context with XML, metadata, and agile development.

Table of Contents:
What is a Data Model?; Why Do We Need a Data Model?; What Camera Settings Also Apply to a Data Model?; What Are Entities?; What Are Data Elements?; What Are Relationships?; What Are Keys?; What Are Subject Area Models?; What Are Logical Data Models?; What Are Physical Data Models?; Which Templates Can Help with Capturing Requirements?; What is the Data Model Scorecard(R); How Can We Work Effectively with Others?; What is Unstructured Data?; What is UML?; What Are the Top 5 Most Frequently Asked Questions?

About the Author :
Steve Hoberman balances the formality and precision of data modeling with the realities of building software systems with severe time, budget, and people constraints. In his consulting and teaching, he focuses on templates, tools, and guidelines to reap the benefits of data modeling with minimal investment. He taught his first data modeling class in 1992 and has educated more than 10,000 people about data modeling and business intelligence techniques since then, spanning every continent except Africa and Antarctica. Steve is the author of seven books on data modeling, including the bestseller Data Modeling Made Simple. He is the founder of the Design Challenges group, inventor of the Data Model Scorecard(R), Conference Chair of the Data Modeling Zone conference, recipient of the 2012 Data Administration Management Association (DAMA) International Professional Achievement Award, and highest rated presenter at Enterprise Data World 2014. Steve can be reached at me@stevehoberman.com, @DataMdlRockStar on Twitter, or through Steve Hoberman on Linked-In.

Review :
Watch the author describe this informative book in this short video. Data Modeling Made Simple will provide the business or IT professional with a practical working knowledge of data modeling concepts and best practices.


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Product Details
  • ISBN-13: 9780977140060
  • Publisher: Technics Publications LLC
  • Publisher Imprint: Technics Publications LLC
  • Height: 180 mm
  • No of Pages: 360
  • Returnable: N
  • Sub Title: A Practical Guide for Business & IT Professionals: 2nd Edition
  • Width: 260 mm
  • ISBN-10: 0977140067
  • Publisher Date: 01 Aug 2009
  • Binding: Paperback
  • Language: English
  • Returnable: N
  • Returnable: N
  • Weight: 734 gr


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