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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

In-memory versus in-database analytics

Spotfire supports in-memory and in-database analytics. So far in this book, we have only been using in-memory data and analytics. Spotfire's in-memory data engine is highly optimized for working with small, medium, and large datasets, but eventually, your computer is likely to run out of memory if you have very large datasets. People often ask me: how large is a very large dataset? Or how much data can Spotfire work with in-memory? For me, this is one of the most difficult questions to answer!

It really depends on how many rows and how many columns of data you are working with. I generally find that the Spotfire in-memory data engine can handle hundreds of millions of rows of data with tens of columns, or hundreds of thousands of rows with thousands of columns. If a dataset is bigger than that, then I recommend using in-database analytics...

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