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Data Modeling Made Simple

A Practical Guide for Business & IT Professionals: 2nd Edition

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. Les mer
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Paperback
Legg i
Paperback
Legg i
Vår pris: 553,-

(Paperback) Fri frakt!
Leveringstid: Sendes innen 7 virkedager
På grunn av Brexit-tilpasninger og tiltak for å begrense covid-19 kan det dessverre oppstå forsinket levering.

Om boka

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.

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Innholdsfortegnelse

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?