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This book enables you to get the very best from TIBCO Spotfire! It is available for order from here: TIBCO Spotfire: A Comprehensive Primer (Second Edition) (Packt Publishing), either in e-book or printed form, or from Amazon.co.uk or Amazon.com |
Sample Data
Wherever possible, the data used for the examples in the book is garnered from public sources. However, a few datasets are no longer available publicly (since publication), or were constructed for the book. You can access the sample data here: TIBCO Spotfire Primer - Sample Data
Please also refer to the Errata below. The data used for the scatter plot in Chapter 2 is not available from its original source - the page was updated shortly after the book was published. It will not be possible to complete the example without referring to the errata.
Chapter Outline
1 - Welcome to Spotfire
Getting started with TIBCO Spotfire | The different Spotfire clients | Importing and loading data into Spotfire | The Spotfire recommendations engine | Simple visualization types | Building useful visualizations | Introduction to marking and filtering | Gaining insights from your data
2 - It's all about the data
Understanding the basic row/column structure of a data table | Exploring key data types | Building a scatter plot with real-world data | Combining data | Population Growth vs Child Mortality | Working with natural hierarchies in data | Gaining insight from the scatter plot | Displaying information quickly in tabular form | Enriching visualizations with color categorization | Visualizing hierarchical data using treemaps
3 - Impactful Dashboards!
KPI Charts | Framig your analysis using text areas | Custom expressions | Document properties | Property controls | Marking | Enabling end-users to interactively configure a KPI chart | Deep dive into the insights you can find in a dashboard | Publishing a dashboard to Spotfire Web | Introduction to the Spotfire library
4 - Sharing insights and collaborating with others
Bookmarks | Annotations | Conversations
5 - Practical Applications of Spotfire Visualizations
Real-world examples of some common Spotfire visualization types | What to use each visualization for | The pros and cons of the visualization types | Configuration hints and tips | Common pitfalls and things to avoid
6 - The Big Wide World of Spotfire
An overview of Spotfire components and architecture | Scalability of Spotfire's Web Player | A quick guide to administration manager | Library administration | Automating tasks using Automation Services
7 - Source Data is Never Enough
Creating metrics using calculated columns | The Spotfire data canvas | Dimensional hierarchies | Categorizing continuous numerical data using binning functions | Slicing and dicing data using hierarchy nodes | Tall tables versus wide tables | Transforming data through pivots and unpivots
8 - The World is Your Visualization
Data relations and marking and filtering between multiple tables | Column matching (for using multiple data tables in one visualization) | Subsets | Showing/hiding data in a visualization | 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 and dendrograms | Profiling data using parallel coordinate plots
9 - What's Your Location?
Creating map charts | Map chart layers | Coordinate reference systems | Using geocoding to position data on a map | Case study ? when geocoding doesn't work | 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
10 - Information Links and Data Connectors
In memory versus in database analytics | Information Links | Database Connectors | Streaming Data
11 - Scripting, Advanced Analytics and Extensions
Scripting in Spotfire - why do it? How can you do it? What can you do with it? | IronPython scripting | JavaScript scripting | Spotfire's Developer Tools | Script trust | TIBCO Enterprise Runtime for R and open-source R | Python | Statistica | Extending Spotfire | The JavaScript API | Server APIs
12 - Scaling the Infrastructure; Keeping Data up to Date
Spotfire server topology | Scaling the Spotfire server using clustering | Spotfire Sites | Web player scalability - Scheduling and routing, Nodes and Services, Resource pools
13 - Beyond the Horizon
Natural Language Search | Canvas styling and theming | Exporting from Spotfire | JavaScript visualizations | Alerting in Spotfire | Additional software products - TIBCO Data Science, Data Virtualization (and more) | TIBCO Cloud Enterprise
Endorsements
Andrew knows Spotfire inside out. He knows configuration options, extension points and APIs, better than anyone I know in the world. Andrew is an experienced and effective end user of Spotfire, and he understands how Spotfire works under the hood. He has developed several areas of new functionality in Spotfire ? both as field extensions and product components. He played a crucial role in the development of the AI-Powered Recommendations engine that was launched in Spotfire X (10).
In this book, Andrew takes the reader on a journey, working with analytics in Spotfire as an analyst and an author. His passion for all things to do with Spotfire shines through every paragraph. The book has something for everyone ? for folks beginning their visual analytics journey, all the way to experts looking to extend Spotfire in sophisticated and elegant ways.
In my experience working across industries to solve complex tech and business problems, there is always a way to get there with Spotfire. This was the source of my original addiction to Spotfire, and remains so to this day. Spotfire?s power, in the hands of experts, allows me to approach every single problem that comes my way with excitement and confidence in a solution. Andrew has been a big part of this ? what I?ve learned from him and how we can take on any challenge that comes our way. I?m super excited about this book and have zero hesitation in recommending it to everyone interested in the field of visual analytics.
Michael O'Connell
Chief Analytics Officer, TIBCO
Errata
As with any book, mistakes inevitably creep in! Since the book was published, some errors have come to light. Any known errors will be detailed here and kept up to date. The short link to this page is: http://community.spotfire.com/s/article/TIBCO-Spotfire-A-Comprehensive-Primer-Second-Edition-by-Andrew-Berridge
Chapter 1 - Incorrect Screenshot
Step number 7 page 42, the screenshot should be:
Chapter 1 - Titanic Data no Longer Available
titanic3.xls is now available in resources
Chapter 2 - Data no Longer Available
The main example for producing a scatter plot showing population growth vs. child mortality refers to the following link (p.61):
https://ourworldindata.org/world-population-growth/
Unfortunately, the page was updated shortly after the book was published, so the source data for the chapter is no longer available from it. You can see an archived version of the web page here:
https://web.archive.org/web/20190331013507/https://ourworldindata.org/world-population-growth
You can also download the data from the visualization shown in the book from this archived link:
Alternatively, the data file is available directly from this page on the TIBCO Community: TIBCO Spotfire Primer - Sample Data
Chapter 3 - Building a details visualization using marking
Page 134, step 3. The expression for the y-axis of the chart should be Avg([close])
Chapter 12 - Scaling the Spotfire Server using clustering
This section of the book discusses clustering Spotfire servers and refers to TIBCO ActiveSpaces®. This product is no longer used for clustering of Spotfire Servers. Instead, Apache Ignite is used. The TIBCO Server Installation and Administration Guide notes that:
Clustering is implemented using Apache Ignite. Apache Ignite clustering requires no manual configuration. It provides TLS version 1.2 for communication, and it is faster than previous clustering solutions. In addition, it looks for specific nodes by using their IP address, rather than discovering any node that communicates using multicasting.
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