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

Connecting SQL Server query to QlikSense Desktop


We are now ready to connect QlikSense to the inventory query we created in the previous section. When first launching QlikSense we are prompted with a message to CREATE A NEW APP as seen in the following screenshot:

We can go then go ahead and name our application AdventureWorks Inventory Dashboard as seen in the following screenshot:

We can then go ahead with creating the application and opening it up. Upon initial load, QlikSense gives developers two different options for adding data, as seen in the following screenshot:

For our purposes we will utilize the Data load editor method because it gives us a better opportunity to leverage the existing query we built with SQL Server. Even though it is a bit more of a manual process than the Add data method,, which is more of an automated and graphical method, using the Data load editor will also help lend insight to how data is loaded into QlikSense.

Once we are in the Data load editor method...