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TIBCO Spotfire: A Comprehensive Primer

TIBCO Spotfire: A Comprehensive Primer

By : Berridge, Phillips
3.6 (8)
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TIBCO Spotfire: A Comprehensive Primer

TIBCO Spotfire: A Comprehensive Primer

3.6 (8)
By: Berridge, Phillips

Overview of this book

The need for agile business intelligence (BI) is growing daily, and TIBCO Spotfire® combines self-service features with essential enterprise governance and scaling capabilities to provide best-practice analytics solutions. Spotfire is easy and intuitive to use and is a rewarding environment for all BI users and analytics developers. Starting with data and visualization concepts, this book takes you on a journey through increasingly advanced topics to help you work toward becoming a professional analytics solution provider. Examples of analyzing real-world data are used to illustrate how to work with Spotfire. Once you've covered the AI-driven recommendations engine, you'll move on to understanding Spotfire's rich suite of visualizations and when, why and how you should use each of them. In later chapters, you'll work with location analytics, advanced analytics using TIBCO Enterprise Runtime for R®, how to decide whether to use in-database or in-memory analytics, and how to work with streaming (live) data in Spotfire. You'll also explore key product integrations that significantly enhance Spotfire's capabilities.This book will enable you to exploit the advantages of the Spotfire serve topology and learn how to make practical use of scheduling and routing rules. By the end of this book, you will have learned how to build and use powerful analytics dashboards and applications, perform spatial analytics, and be able to administer your Spotfire environment efficiently
Table of Contents (18 chapters)
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1
Section 1: Introducing Spotfire
6
Section 2: Spotfire In Depth
12
Section 3: Databases, Scripting, and Scaling Spotfire

Mashing up data from different tables in a single visualization

Spotfire allows you to combine data from multiple tables in the same visualization and automatically matches any columns with the same name and data type. You can also manually match columns with different names or data types that you know to be equivalent.

If the columns that you want to use from the two data tables match, then the operation is very easy: you pick the columns you want from the table you want. Continuing with the HICP data we used in the previous example, let's explore this together:

  1. In order to demonstrate this concept, let's create an issue with the data in the Main data table artificially. Open the data panel and delete the Alcohol & Tobacco column from the Main data table by right-clicking on it and choosing Delete:

By deleting a column, we have made it no longer available in...

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