Data Modeling Made Simple
A Practical Guide for Business & IT Professionals: 2nd Edition
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(Paperback)
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På grunn av Brexit-tilpasninger og tiltak for å begrense covid-19 kan det dessverre oppstå forsinket levering.
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.
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?