Practical Business Intelligence: Optimize Business Intelligence for Efficient Data Analysis

Learn to get the most out of your business data to optimize your business

Key Features

• [*] This book will enable and empower you to break free of the shackles of spreadsheets
• [*] Learn to make informed decisions using the data at hand with this highly practical, comprehensive guide
• [*] This book includes real-world use cases that teach you how analytics can be put to work to optimize your business
• [*] Using a fictional transactional dataset in raw form, you’ll work your way up to ultimately creating a fully-functional warehouse and a fleshed-out BI platform

Book DescriptionBusiness 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.

What you will learn

• [*] Create a BI environment that enables self-service reporting
• [*] Understand SQL and the aggregation of data
• [*] Develop a data model suitable for analytical reporting
• [*] Connect a data warehouse to the analytic reporting tools
• [*] Understand the specific benefits behind visualizations with D3.js, R, Tableau, QlikView, and Python
• [*] Get to know the best practices to develop various reports and applications when using BI tools
• [*] Explore the field of data analysis with all the data we will use for reporting

Who this book is for

This book is for anyone who has wrangled with data to try to perform automated data analysis through visualizations for themselves or their customers. This highly-customized guide is for developers who know a bit about analytics but don't know how to make use of it in the field of business intelligence.