Book Image

Practical Business Intelligence

Book Image

Practical Business Intelligence

Overview of this book

Business Intelligence (BI) is at the crux of revolutionizing enterprise. Everyone wants to minimize losses and maximize profits. Thanks to Big Data and improved methodologies to analyze data, Data Analysts and Data Scientists are increasingly using data to make informed decisions. Just knowing how to analyze data is not enough, you need to start thinking how to use data as a business asset and then perform the right analysis to build an insightful BI solution. Efficient BI strives to achieve the automation of data for ease of reporting and analysis. Through this book, you will develop the ability to think along the right lines and use more than one tool to perform analysis depending on the needs of your business. We start off by preparing you for data analytics. We then move on to teach you a range of techniques to fetch important information from various databases, which can be used to optimize your business. The book aims to provide a full end-to-end solution for an environment setup that can help you make informed business decisions and deliver efficient and automated BI solutions to any company. It is a complete guide for implementing Business intelligence with the help of the most powerful tools like D3.js, R, Tableau, Qlikview and Python that are available on the market.
Table of Contents (16 chapters)
Practical Business Intelligence
Credits
About the Author
About the Reviewer
www.PacktPub.com
Customer Feedback
Preface

Performing stored procedures in SQL Server


Stored procedures are a set of scripts that can run at a click of a button to perform a specific task. Stored procedures are great to use for many reasons, especially when it comes to manual tasks. They help automate manual tasks and make things run more efficiently.

Note

To learn more about stored procedures in Microsoft SQL Server, visit the following website: https://msdn.microsoft.com/en-us/library/ms345415.aspx.

In the previous example, we had to manually enter the values for the three countries that were to be used as columns. Additionally, we had to format them in the following manner:

[Canada], [France], [United Kingdom] 

Well, what if the database had an update and changed the naming for United Kingdom to UK instead? Our script would need to be updated. Also, if we wanted to include all of the countries as columns, we would need to use the following list:

[Australia],[Canada],[France],[Germany],[United Kingdom],[United States] 

If...