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Microsoft SQL Server 2014 Business Intelligence Development Beginner's Guide

You're reading from   Microsoft SQL Server 2014 Business Intelligence Development Beginner's Guide Get to grips with Microsoft Business Intelligence and Data Warehousing technologies using this practical guide

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Product type Paperback
Published in May 2014
Publisher
ISBN-13 9781849688888
Length 350 pages
Edition Edition
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Authors (2):
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Reza Rad Reza Rad
Author Profile Icon Reza Rad
Reza Rad
Abolfazl Radgoudarzi Abolfazl Radgoudarzi
Author Profile Icon Abolfazl Radgoudarzi
Abolfazl Radgoudarzi
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Table of Contents (19) Chapters Close

Microsoft SQL Server 2014 Business Intelligence Development Beginner's Guide
Credits
About the Author
About the Reviewers
www.PacktPub.com
Preface
1. Data Warehouse Design 2. SQL Server Analysis Services Multidimensional Cube Development FREE CHAPTER 3. Tabular Model Development of SQL Server Analysis Services 4. ETL with Integration Services 5. Master Data Management 6. Data Quality and Data Cleansing 7. Data Mining – Descriptive Models in SSAS 8. Identifying Data Patterns – Predictive Models in SSAS 9. Reporting Services 10. Dashboard Design 11. Power BI 12. Integrating Reports in Applications Index

Understanding Business Intelligence


Based on Gartner's definition (http://www.gartner.com/it-glossary/business-intelligence-bi/), Business Intelligence is defined as follows:

Business Intelligence is an umbrella term that includes the applications, infrastructure and tools, and best practices that enable access to and analysis of information to improve and optimize decisions and performance.

As the definition states, the main purpose of a BI system is to help decision makers to make proper decisions based on the results of data analysis provided by the BI system.

Nowadays, there are many operational systems in each industry. Businesses use multiple operational systems to simplify, standardize, and automate their everyday jobs and requirements. Each of these systems may have their own database, some of which may work with SQL Server, some with Oracle. Some of the legacy systems may work with legacy databases or even file operations. There are also systems that work through the Web via web services and XML. Operational systems are very useful in helping with day-to-day business operations such as the process of hiring a person in the human resources department, and sale operations through a retail store and handling financial transactions.

The rising number of operational systems also adds another requirement, which is the integration of systems together. Business owners and decision makers not only need integrated data but also require an analysis of the integrated data. As an example, it is a common requirement for the decision makers of an organization to compare their hiring rate with the level of service provided by a business and the customer satisfaction based on that level of service. As you can see, this requirement deals with multiple operational systems such as CRM and human resources. The requirement might also need some data from sales and inventory if the decision makers want to bring sales and inventory factors into their decisions. As a supermarket owner or decision maker, it would be very important to understand what products in which branches were in higher demand. This kind of information helps you to provide enough products to cover demand, and you may even think about creating another branch in some regions.

The requirement of integrating multiple operational systems together in order to create consolidated reports and dashboards that help decision makers to make a proper decision is the main directive for Business Intelligence.

Some organizations and businesses use ERP systems that are integrated, so a question may appear in your mind that there won't be a requirement for integrating data because consolidated reports can be produced easily from these systems. So does that mean that these systems still require a BI solution? The answer in most cases is yes. The companies or businesses might not require a separate BI system for internal and parts of the operations that implemented it through ERP. However, they might require getting some data from outside, for example, getting some data from another vendor's web service or many other protocols and channels to send and receive information. This indicates that there would be a requirement for consolidated analysis for such information, which brings the BI requirement back to the table.

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