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Spotfire Data Science

Spotfire Data Science
Formerly TIBCO Data Science with Team Studio and Statistica

Overview

What is Spotfire Data Science?

Spotfire Data Science (formerly TIBCO Data Science) is a comprehensive platform for operationalizing data science, allowing users to scale data science across an organization to solve complex challenges faster and speed innovation. It is designed to enable data scientists to…

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Recent Reviews

Positive experience

7 out of 10
September 04, 2018
Incentivized
Data Science is being used for the more complicated optimization and control improvements. It allows the use of advanced mathematical …
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TIBCO Data Science

8 out of 10
January 30, 2018
Incentivized
Our organization uses TIBCO Data Science mainly in our water quality and biological departments. We use this program to help with the …
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Mostly Satisfied

7 out of 10
November 08, 2017
Incentivized
Data Science has allowed us to rapidly deploy advanced analytics to support a growing organization, using a team of non-programmers to …
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Pricing

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What is Spotfire Data Science?

Spotfire Data Science (formerly TIBCO Data Science) is a comprehensive platform for operationalizing data science, allowing users to scale data science across an organization to solve complex challenges faster and speed innovation. It is designed to enable data scientists to create innovative…

Entry-level set up fee?

  • No setup fee

Offerings

  • Free Trial
  • Free/Freemium Version
  • Premium Consulting/Integration Services

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Product Details

What is Spotfire Data Science?

Spotfire Data Science (formerly TIBCO Data Science) is a comprehensive platform for operationalizing data science, allowing users to scale data science across an organization to solve complex challenges faster and speed innovation. It is designed to enable data scientists to create innovative solutions using the latest machine learning techniques and open source developments. Create ML pipelines using a point-and-click UI or code. Orchestrate analytics using the tools, languages, and any frameworks of choice. Then deploy, manage, and govern models across core and distributed data environments to deliver insights and act with confidence.

Spotfire Data Science Features

Platform Connectivity Features

  • Supported: Connect to Multiple Data Sources
  • Supported: Extend Existing Data Sources
  • Supported: Automatic Data Format Detection
  • Supported: MDM Integration

Data Exploration Features

  • Supported: Visualization
  • Supported: Interactive Data Analysis

Data Preparation Features

  • Supported: Interactive Data Cleaning and Enrichment
  • Supported: Data Transformations
  • Supported: Data Encryption
  • Supported: Built-in Processors

Platform Data Modeling Features

  • Supported: Multiple Model Development Languages and Tools
  • Supported: Automated Machine Learning
  • Supported: Single platform for multiple model development
  • Supported: Self-Service Model Delivery

Model Deployment Features

  • Supported: Flexible Model Publishing Options
  • Supported: Security, Governance, and Cost Controls

Additional Features

  • Supported: End-to-End Analytics Platform
  • Supported: Model Management and Governance
  • Supported: Validated Analytics (GxP, FDA Compliant)

Spotfire Data Science Screenshots

Screenshot of Reusable Workspace TemplateScreenshot of AutoML - Create Editable Workflows for Feature Selection/Generation, Model Creation/Selection, Hyperparameter TuingScreenshot of Interactive DashboardScreenshot of Orchestrate Analytics across Amazon, Google, and Microsoft

Spotfire Data Science Videos

Spotfire Data Science - Statistica

Watch Spotfire Data Science - Team Studio

Spotfire Data Science Technical Details

Deployment TypesOn-premise, Software as a Service (SaaS), Cloud, or Web-Based
Operating SystemsWindows
Mobile ApplicationNo

Frequently Asked Questions

Alteryx, RapidMiner, and Dataiku are common alternatives for Spotfire Data Science.

Reviewers rate Connect to Multiple Data Sources and Extend Existing Data Sources and Automatic Data Format Detection highest, with a score of 9.1.

The most common users of Spotfire Data Science are from Enterprises (1,001+ employees).
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Comparisons

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Reviews and Ratings

(34)

Attribute Ratings

Reviews

(1-1 of 1)
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Score 8 out of 10
Vetted Review
Verified User
Incentivized
At my current company, TIBCO Data Science is being used by at least two senior scientists that are located in different departments. Those senior scientists (including myself) use the software to answer analytical questions about issues related to water quality, toxicology, conservation biology, and other areas in support of our public and private sector clients. At my previous company, I managed several junior staff who were also TIBCO Data Science users for the same types of questions, but the cost of the software is a handicap toward getting more junior users at my current company.
  • It can run batch statistics for multiple parameters and stations with one button click, as long as the data are set up correctly. It is a major time saver.
  • Its graphics are usually much more editable than other statistical software, except for those that need programming.
  • It has a very good "textbook" that gives the ins and outs of each analysis. Other software may use a generic test name without giving the specific references for the formulas that it is based on.
  • Although the graphics can be copied into Word or Excel, the copying and pasting process is buggy. Sometimes I basically have to do a Capture Rectangle of a graphic and paste it as a jpg, rather than having an embedded and editable graphic in my Word document.
  • The dialog boxes for some of the common tests, like multiple regression and ANOVA, use quirky terminology that is not intuitive to new users coming out of grad school with a more updated education. I have been using it for over ten years, and the dialogs have not updated in all of that time.
  • The tests like NMDS and PCA are clunky and difficult to use and get the appropriate outputs, especially compared to specialized software like PRIMER.
It is good for exploring data and producing a large number of similar analyses for groups of stations and parameters. It is also helpful for projects that produce similar graphics each year with just minor data updates because the graphs can be rerun with minimal clicking. It does not work as well for specialized analyses and transparency of certain choices in the parameters that are being chosen in the background.
  • For exploring large datasets with minimal set-up time, it works very well. There is no programming needed, and the graphics can be made to look professional with some editing. This helps stay within budget for data analysis.
  • If both senior and junior staff have access to the software, then senior staff can explore and decide on the final analysis and junior staff can make the manual tweaks needed for the final product.
  • SAS, S-Plus, PRIMER, R program and MATLAB
In the past, cost, ease of use, and versatility were what made me choose Data Science. However, the cost concern may be leading my company to pursue solutions like R programming instead.
2
Senior and Expert Scientists
I have never spoken to a Data Science support person.
  • Exploratory data analysis of water quality data
  • Impact analysis for environmental data
The company is hesitant to spend this much on software. They are primarily an engineering firm, and they don't understand the use of analytical software for environmental professionals.
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