Book Image

Practical Business Intelligence

By : Ahmed Sherif
Book Image

Practical Business Intelligence

By: Ahmed Sherif

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

Summary


We have come to the conclusion of another chapter. We started with a simple MS SQL Server query and turned it into a fully functional dashboard. Our original query only had ten rows of data, but that turned out to be sufficient enough to tell a story about how the sales revenue was distributed amongst different marketing strategies. Tableau helped us isolate different visualizations separately and then combine them into a single dashboard where all three components interacted with each other. Finally, through the Tableau Public portal, we saw how easily we could publish our results and share them with the rest of the world. In the next chapter, we will continue with the desktop discovery genre and focus our attention to the tool that is considered the closest competitor to Tableau: QlikSense. We will build an inventory dashboard for AdventureWorks that will be used to alert managers when certain products are running low and need to be reordered.