This Business Intelligence Guidebook: From Data Integration to Analytics, pdf, ebook, ePub, and free download by Rick Sherman is a reference for business people, students, and also students. The following is an important review to read.
Table of Contents
Intro
Intelligence in the business world is an important thing that is the basis for carrying out business entrepreneurial activities. The rapid development of the times, with the rise of the free market economic system began, made business science a branch of science that was in great demand by many people living in contemporary times.
The things that are the basis for business science are how to create something that can attract many people to buy or use the services provided by entrepreneurs.
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For this reason, optimal intelligence is needed in carrying out business activities in today’s world. The free market system that is currently rampant in the present era certainly provokes entrepreneurs to always be ready to compete in terms of innovations issued by each individual. Without innovation, business activity will not get optimal results because there is no new thing related to the size of the market amid social life.

Book Description
In this case, a professional writer named Rick Sherman created a breakthrough in the business world by issuing a book entitled Business Intelligence Guidebook: From Data Integration to Analytics by Rick Sherman.
This book raises topics that are rarely discussed amid society. Through accurate big data, this book provides a lot of information about the business. Extensive knowledge of business matters can be one way to advance the business and can maintain the profit graph obtained by the company.
Accurate data sources are also one the important things in developing a business strategy that is ready to run. Extensive knowledge and acumen in terms of business analysis can form a tough attitude and character for entrepreneurs. Wise decision-making is also a determinant for the development or not of a business entrepreneur activity, due to the many methods offered by various world economists related to business matters, it is necessary to decide something carefully and consistently.
Through the Amazon website, information related to this book is quoted, namely:
Between the high-level concepts of business intelligence and the nitty-gritty instructions for using vendors’ tools lies the essential, yet a poorly-understood layer of architecture, design, and process. Without this knowledge, Big Data is belittled – projects flounder, are lat,e and go over budget. Business Intelligence Guidebook: From Data Integration to Analytics shines a bright light on an often neglected topic, arming you with the knowledge you need to design rock-solid business intelligence and data integration processes. Practicing consultant and adjunct BI professor Rick Sherman takes the guesswork out of creating systems that are cost-effective, reusable, and essential for transforming raw data into valuable information for business decision-makers.
After reading this book, you will be able to design the overall architecture for functioning business intelligence systems with supporting data warehousing and data-integration applications. You will have the information you need to get a project launched, developed, managed, and delivered on time and budget – turning the deluge of data into actionable information that fuels business knowledge. Finally, you’ll give your career a boost by demonstrating an essential knowledge that puts corporate BI projects on a fast-track to success.
For readers who are interested in this book, you can look for it in the nearest shops or you can also buy it online through Amazon. The book, published by Morgan Kaufmann’s publishing team, is very suitable for students majoring in business or entrepreneurship. With a price range of around 54.95 dollars.
Table of Contents
Foreword
How to Use This Book
Acknowledgments
Part I. Concepts and Context
Chapter 1. The Business Demand for Data, Information, and Analytics
Just One Word: Data
Welcome to the Data Deluge
Taming the Analytics Deluge
Too Much Data, Too Little Information
Data Capture versus Information Analysis
The Five Cs of Data
Common Terminology from our Perspective
Part II. Business and Technical Needs
Chapter 2. Justifying BI: Building the Business and Technical Case
Why Justification is Needed
Building the Business Case
Building the Technical Case
Assessing Readiness
Creating a BI Road Map
Developing Scope, Preliminary Plan, and Budget
Obtaining Approval
Common Justification Pitfalls
Chapter 3. Defining Requirements—Business, Data and Quality
The Purpose of Defining Requirements
Goals
Deliverables
Roles
Defining Requirements Workflow
Interviewing
Documenting Requirements
Part III. Architectural Framework
Chapter 4. Architecture Framework
The Need for Architectural Blueprints
Architectural Framework
Information Architecture
Data Architecture
Technical Architecture
Product Architecture
Metadata
Security and Privacy
Avoiding Accidents with Architectural Planning
Do Not Obsess over the Architecture
Chapter 5. Information Architecture
The Purpose of an Information Architecture
Data Integration Framework
DIF Information Architecture
Operational BI versus Analytical BI
Master Data Management
Chapter 6. Data Architecture
The Purpose of a Data Architecture
History
Data Architectural Choices
Data Integration Workflow
Data Workflow—Rise of EDW Again
Operational Data Store
Chapter 7. Technology & Product Architectures
Where are the Product and Vendor Names?
Evolution Not Revolution
Technology Architecture
Product and Technology Evaluations
Part IV. Data Design
Chapter 8. Foundational Data Modeling
The Purpose of Data Modeling
Definitions—The Difference Between a Data Model and Data Modeling
Three Levels of Data Models
Data Modeling Workflow
Where Data Models Are Used
Entity-Relationship (ER) Modeling Overview
Normalization
Limits and Purpose of Normalization
Chapter 9. Dimensional Modeling
Introduction to Dimensional Modeling
High-Level View of a Dimensional Model
Facts
Dimensions
Schemas
Entity Relationship versus Dimensional Modeling
Purpose of Dimensional Modeling
Fact Tables
Achieving Consistency
Advanced Dimensions and Facts
Dimensional Modeling Recap
Chapter 10. Business Intelligence Dimensional Modeling
Introduction
Hierarchies
Outrigger Tables
Slowly Changing Dimensions
Causal Dimension
Multivalued Dimensions
Junk Dimensions
Value Band Reporting
Heterogeneous Products
Alternate Dimensions
Too Few or Too Many Dimensions
Part V. Data Integration Design
Chapter 11. Data Integration Design and Development
Getting Started with Data Integration
Data Integration Architecture
Data Integration Requirements
Data Integration Design
Data Integration Standards
Loading Historical Data
Data Integration Prototyping
Data Integration Testing
Chapter 12. Data Integration Processes
Introduction: Manual Coding versus Tool-Based Data Integration
Data Integration Services
Part VI. Business Intelligence Design
Chapter 13. Business Intelligence Applications
BI Content Specifications
Revise BI Applications List
BI Personas
BI Design Layout—Best Practices
Data Design for Self-Service BI
Matching Types of Analysis to Visualizations
Chapter 14. BI Design and Development
BI Design
We have already found information in the complete table of contents of this book. The table of contents really helps the reader know the topics presented in this book.
You can read the full Elsevier page.
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About the Author
For the book’s author information, we found the source from the Rocketreach page. Although it is not complete, the information about the author is enough to help you get to know him.
Rick Sherman is the founder of Athena IT Solutions, which provides services in the areas of consulting, training, and vendors for business intelligence, analytics, data integration, and data warehousing. Athena IT Solutions helps businesses increase the intelligence of their business decisions through data warehousing and business intelligence consulting.
Our services include Detailed data warehousing & business intelligence assessments that ensure that projects have the best chance for success and stay within budget. Full-scale implementation and consulting for the advice, planning, management, and development to see projects through completion.
Onsite Business intelligence and data warehousing education for technical staff and business users. Vendor services lend the credibility of a published industry expert to your client presentations, webinars, and white papers. We will also assess your products and marketing strategies. He is also an additional faculty member at a Northeastern University Graduate School of Engineering and is often involved in contributing to industry publications, events, and webinars.
Product Details
- Publisher : Morgan Kaufmann; 1st edition (November 21, 2014)
- Language : English
- Paperback : 550 pages
- ISBN-10 : 012411461X
- ISBN-13 : 978-0124114616
- Item Weight : 2.12 pounds
- Dimensions : 7.5 x 1.24 x 9.25 inches

Where to Buy Books
Before we tell you where to buy this book, you should know that there are several versions of this book published. First, the Digital version, and secondly, the print version (paperback & hardcover).
To buy this book, you can come to the nearest book shop. Let’s ask in a subscription bookstore, whether to sell it.
Many people shop for books on Amazon and eBay. Some use an online shopping system.
PDF Free eBook Download
The digital edition can be accessed via the internet. The files are in the form of PDFs, eBooks, Epub, Doc, and others. Everything can be read through a computer device. Different with books in Kindle format that must be read using a special device issued by the Amazon company.
The free download link of this Business Intelligence Guidebook: From Data Integration to Analytics cannot be accessed if the issuing company does not give permission. The solution, is you need to buy in a bookstore.
Conclusion
For students or entrepreneurs who want to improve their skills in business activities, this book is very relevant to be used as reading material with the aim of enriching the understanding of the principles in the business world in contemporary times.