Book Image

TIBCO Spotfire: A Comprehensive Primer. - Second Edition

By : Andrew Berridge, Michael Phillips
Book Image

TIBCO Spotfire: A Comprehensive Primer. - Second Edition

By: Andrew Berridge, Michael 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)
Free Chapter
1
Section 1: Introducing Spotfire
6
Section 2: Spotfire In Depth
12
Section 3: Databases, Scripting, and Scaling Spotfire

Drilling in to the KPI chart

Remember the introduction to the section on KPI charts? I stated that KPI charts give you the answer to the "What?" question. Now, let's look at the "Why?" of analytics.

Answering the "Why?" question can be a lot more challenging than answering the "What?". Sometimes, significant creativity is required, but here's a checklist of things you might wish to consider:

  • What types of visualizations will best show a detailed view of the data?
  • How can I slice and dice the details visualizations to show a complete picture?
  • Can additional value be gained by showing multiple, related datasets side by side?

We will build a line chart details visualization that shows historical data over time. By way of an example, I will walk you through the thought processes that go into making the line chart more and more insightful...