Data Modeling for the Business: A Handbook for Aligning the Business with IT using High-Level Data Models

Did you ever try getting Businesspeople and IT to agree on the project scope for a new application? Or try getting Marketing and Sales to agree on the target audience? Or try bringing new team members up to speed on the hundreds of tables in your data warehouse -- without them dozing off?

Whether you are a businessperson or an IT professional, you can be the hero in each of these and hundreds of other scenarios by building a High-Level Data Model. The High-Level Data Model is a simplified view of our complex environment. It can be a powerful communication tool of the key concepts within our application development projects, business intelligence and master data management programs, and all enterprise and industry initiatives.

Learn about the High-Level Data Model and master the techniques for building one, including a comprehensive ten-step approach and hands-on exercises to help you practice topics on your own. In this book, we review data modeling basics and explain why the core concepts stored in a high-level data model can have significant business impact on an organization. We explain the technical notation used for a data model and walk through some simple examples of building a high-level data model. We also describe how data models relate to other key initiatives you may have heard of or may be implementing in your organization.

This book contains best practices for implementing a high-level data model, along with some easy-to-use templates and guidelines for a step-by-step approach. Each step will be illustrated using many examples based on actual projects we have worked on. Names have been changed to protect the innocent, but the pain points and lessons have been preserved. One example spans an entire chapter and will allow you to practice building a high-level data model from beginning to end, and then compare your results to ours.

Building a high-level data model following the ten step approach you'll read about is a great way to ensure you will retain the new skills you learn in this book.

As is the case in many disciplines, using the right tool for the right job is critical to the overall success of your high-level data model implementation. To help you in your tool selection process, there are several chapters dedicated to discussing what to look for in a high-level data modeling tool and a framework for choosing a data modeling tool, in general.

This book concludes with a real-world case study that shows how an international energy company successfully used a high-level data model to streamline their information management practices and increase communication throughout the organization--between both businesspeople and IT.

1100036414
Data Modeling for the Business: A Handbook for Aligning the Business with IT using High-Level Data Models

Did you ever try getting Businesspeople and IT to agree on the project scope for a new application? Or try getting Marketing and Sales to agree on the target audience? Or try bringing new team members up to speed on the hundreds of tables in your data warehouse -- without them dozing off?

Whether you are a businessperson or an IT professional, you can be the hero in each of these and hundreds of other scenarios by building a High-Level Data Model. The High-Level Data Model is a simplified view of our complex environment. It can be a powerful communication tool of the key concepts within our application development projects, business intelligence and master data management programs, and all enterprise and industry initiatives.

Learn about the High-Level Data Model and master the techniques for building one, including a comprehensive ten-step approach and hands-on exercises to help you practice topics on your own. In this book, we review data modeling basics and explain why the core concepts stored in a high-level data model can have significant business impact on an organization. We explain the technical notation used for a data model and walk through some simple examples of building a high-level data model. We also describe how data models relate to other key initiatives you may have heard of or may be implementing in your organization.

This book contains best practices for implementing a high-level data model, along with some easy-to-use templates and guidelines for a step-by-step approach. Each step will be illustrated using many examples based on actual projects we have worked on. Names have been changed to protect the innocent, but the pain points and lessons have been preserved. One example spans an entire chapter and will allow you to practice building a high-level data model from beginning to end, and then compare your results to ours.

Building a high-level data model following the ten step approach you'll read about is a great way to ensure you will retain the new skills you learn in this book.

As is the case in many disciplines, using the right tool for the right job is critical to the overall success of your high-level data model implementation. To help you in your tool selection process, there are several chapters dedicated to discussing what to look for in a high-level data modeling tool and a framework for choosing a data modeling tool, in general.

This book concludes with a real-world case study that shows how an international energy company successfully used a high-level data model to streamline their information management practices and increase communication throughout the organization--between both businesspeople and IT.

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Data Modeling for the Business: A Handbook for Aligning the Business with IT using High-Level Data Models

Data Modeling for the Business: A Handbook for Aligning the Business with IT using High-Level Data Models

Data Modeling for the Business: A Handbook for Aligning the Business with IT using High-Level Data Models

Data Modeling for the Business: A Handbook for Aligning the Business with IT using High-Level Data Models

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Overview

Did you ever try getting Businesspeople and IT to agree on the project scope for a new application? Or try getting Marketing and Sales to agree on the target audience? Or try bringing new team members up to speed on the hundreds of tables in your data warehouse -- without them dozing off?

Whether you are a businessperson or an IT professional, you can be the hero in each of these and hundreds of other scenarios by building a High-Level Data Model. The High-Level Data Model is a simplified view of our complex environment. It can be a powerful communication tool of the key concepts within our application development projects, business intelligence and master data management programs, and all enterprise and industry initiatives.

Learn about the High-Level Data Model and master the techniques for building one, including a comprehensive ten-step approach and hands-on exercises to help you practice topics on your own. In this book, we review data modeling basics and explain why the core concepts stored in a high-level data model can have significant business impact on an organization. We explain the technical notation used for a data model and walk through some simple examples of building a high-level data model. We also describe how data models relate to other key initiatives you may have heard of or may be implementing in your organization.

This book contains best practices for implementing a high-level data model, along with some easy-to-use templates and guidelines for a step-by-step approach. Each step will be illustrated using many examples based on actual projects we have worked on. Names have been changed to protect the innocent, but the pain points and lessons have been preserved. One example spans an entire chapter and will allow you to practice building a high-level data model from beginning to end, and then compare your results to ours.

Building a high-level data model following the ten step approach you'll read about is a great way to ensure you will retain the new skills you learn in this book.

As is the case in many disciplines, using the right tool for the right job is critical to the overall success of your high-level data model implementation. To help you in your tool selection process, there are several chapters dedicated to discussing what to look for in a high-level data modeling tool and a framework for choosing a data modeling tool, in general.

This book concludes with a real-world case study that shows how an international energy company successfully used a high-level data model to streamline their information management practices and increase communication throughout the organization--between both businesspeople and IT.


Product Details

ISBN-13: 9780977140077
Publisher: Technics Publications, LLC
Publication date: 04/01/2009
Series: Take It with You Guides
Edition description: TECHNICS PUBLICATIONS LLC
Pages: 285
Product dimensions: 7.00(w) x 9.90(h) x 0.80(d)

Table of Contents

INTRODUCTION 11
CHAPTER 1:
What is a Data Model? 13
CHAPTER 2:
Why Does a High-Level Data Model Matter? 27
Integration 33
Standards and Reuse 35
Data Modeling for All 37
Now You Try It! Let's Build a High-Level Data Model 38
CHAPTER 3:
A More Detailed Look at the High-Level Data Model 41
Very High-level Data Model (VHDM) 45
High-Level Data Model (HDM) 48
Logical Data Model 53
Physical Data Model 54
How the Four Levels of Detail Fit Together 57
Components of a HDM 60
Now You Try It! Using Concepts and Relationships 70
Dimensional Models 70
Now You Try It! Creating a High-Level Data Model for BI Reporting 74
Some Important Terms 74

CHAPTER 4:
Layout and Formatting Tips for High-Level Data Models 77
Concepts 78
Relationships 80
Other Tips for Effective Model Layout 81
Now You Try It! Understanding High-Level Data Models 84
CHAPTER 5:
What is in a Name? 87
CHAPTER 6:
Different Modeling Notations 91
Entity-Relationship (ER) Modeling 92
Information Engineering (IE) 93
IDEF1X 94
Barker Notation 95
UML Modeling 96
Object Role Modeling (ORM) 99
"Natural-Language" Modeling 101
CHAPTER 7:
How High-Level Data Models Fit With Other Data Initiatives 103
Business Intelligence and Data Warehousing 104
Master Data Management 108
Data Governance 110
Application Development and Agile Methods 112
Enterprise Architecture 114
Process Modeling 114
Now You Try It! Using HDMs in Your Organization's Initiatives 116
CHAPTER 8:
Creating a Successful High-Level Data Model 119
Ten steps to completing the HDM 119
CHAPTER 9:
High-Level Data Model Templates 185
In-The-Know Template 185
Concept List 189
Concept Family Tree 192
Concept Grain Matrix 198
Industry Data Models 201
CHAPTER 10:
Putting the Pieces Together 207
The Ice HDM 208
The Ice Cube HDM 221
CHAPTER 11:
Justifying a Modeling Tool for the High-Level Data Model 233
Metadata 234
Reuse 235
Linking 238
Impact Analysis 240
Automation 241

CHAPTER 12:
Key Modeling Tool Features for the High-Level Data Model 245
Integration with Other Tools 246
Design Layers with Linking Capability 246
Verbalization from the Data Model 247
Sensible Notation for High-Level Data Models 247
Ability to Capture Business Metadata 248
Presentation of Models 248
Repository Integration 248
Ease of Use for Business Users 248
Now You Try It! Creating Your Criteria for a Tools Evaluation 249
CHAPTER 13:
An Approach for Evaluating Modeling Tools 251
Why do we Need to Follow a Selection Method? 252
The Outline Method 252
CHAPTER 14:
Energy Company Case Study 261
The Pain Point 261
Identifying Purpose, Stakeholders, and Goals 262
Implementation 264
Marketing 271
Benefits 273
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