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
About the Author
About the Reviewer
Customer Feedback

Comparing tools head-to-head

We dived deep into six different tools that can be used for BI. As mentioned before, they generally fall under two main categories:

  • Data discovery desktop applications

  • Traditional programming languages

Deciding on the best tool or methodology for our organization largely depends on our needs as well as our BI maturity. Are the users at a level where they need to be spoon-fed the data in a format that is ready to go out the door? Are the users more tech-savvy that just require us to point them in the direction where the raw data is stored and they can do the rest on their own? These are all good questions and will vary based on the organizations, as well as users within the same organization.

Comparing the data discovery desktop applications

We covered three popular data discovery desktop applications:

  • Power BI

  • Tableau Public

  • QlikSense

As we went through an entire exercise of developing a BI application with each one of these tools, we encountered similarities and differences...