IBM Watson is a family of applications which try to bring cognitive services in packages solutions. It includes sophisticated data discovery tools, predictive analytics tools and text-mining tools but also industry-specific solutions such as IBM Watson Health.
It's main components are:
This is probably Stephen Few's most popular book. It clearly explains how to design dashboards for optimal communication of the data and it also shows you lots of examples of badly designed dashboards and how to improve them.
Stephen Few is one of the world's most well-known gurus on data visualization. In this book, he gives a clear overview on how to format tables and matrices and how to design your visualizations for optimal communication. A must read for every business intelligence professional!
One of the best books around on dimensional modelling. Adamson takes you onto a tour around the different types of dimensions and fact tables and clearly explains how to design them and how to construct your ETL. At least as good as the Kimball books.
Window functions are a special construct in the SQL language that allow you to easily calculate more complex requirements, such as year-to-date calculations, moving averages, percentiles and so on.
This book is a very detailed introduction to DAX, the powerful language behind Power Pivot and Power BI. Due to it's clear writing style, the book is an excellent starting point for beginners. However, even DAX pros will get value out of this book.
Mobile business intelligence has been part of everyone’s business intelligence roadmaps for quite some time now. However, until recently, Microsoft didn’t have a solid offering in its SQL Server BI stack that could tackle the specific needs of displaying reports and dashboards on mobile devices. With SQL Server 2016, Microsoft aims to change all this.
