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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

Tall tables versus wide tables

Data tables are row-by-column matrices, and obviously they can range in size from one row by one column to many rows by many columns. You might have come across the colloquial expressions tall table and wide table, or even tall, narrow table and short, wide table, or some variation thereof.

These expressions are a handy way of describing the fundamental way in which the data is structured or categorized in a table. In a tall table, a list of categories is contained under a single column and a second column lists values associated with each of those categories. In a wide table, each category gets its own column and the associated values appear under it.

Consider the airline delay data we used previously in this chapter. As it stands, the data is wide. There is a column for every type of delay, for example:

As a tall table, it looks very different...

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