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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 Small Businesses (1-50 employees).
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Comparisons

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Reviews and Ratings

(34)

Attribute Ratings

Reviews

(1-7 of 7)
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Score 10 out of 10
Vetted Review
Verified User
I use Spotfire Data Science for all of my data analysis and data management needs. Ordinarily, I receive data or get access to my client's database. I import it into Spotfire Data Science and ordinarily repair fundamental problems with the data. Next, I get the data into an analyzable form. This may require writing macros to transform the data. Spotfire Data Science macros are powerful. E.g., in analyzing employee data, I aligned events from eight different datasets relative to hiring date. I perform easier or iterative transformations in a workspace. Many of my problems require prediction so I leverage Spotfire Data Science's different modeling nodes and always end up with a powerful ensemble model. The final model can be exported into whatever code my client prefers. Another common area is need is performing exploratory data analysis. Spotfire Data Science is provides quick results for same day responses to clients.
  • Spotfire Data Science provide reliable results.
  • Spotfire Data Science is 'complete' meaning it provides nearly all the tools I will ever need. If it is not in Spotfire Data Science, then it is probably not worth the effort.
  • Spotfire Data Science saves time on figuring out how to do new things; maintenance; and execution time.
  • Spotfire Data Science can handle large datasets.
  • Spotfire Data Science works more like a quant thinks, so I do not have to trick it to solve the problem in a natural way.
  • I think all statistical software could be better organized by problem rather than tool type. All of the academic books are organized this way so that is how we all think.
Spotfire Data Science is excellent for EDA (Exploratory Data Analysis); handling new data or ongoing data streams; mapping out a complex stream of data processing (using a workspace); and providing fast reliable results.
Score 10 out of 10
Vetted Review
Verified User
Incentivized
Spotfire Data Science is used by our organization to build advanced analytical forecasting and other predictive models and for simple to understand visualizations. The software is used by the professional analysts exclusively, no other group of professionals employs the software. Spotfire Data Science does data science in an easy-to-use, visually appealing style.
  • Spotfire Data Science does the point-and-click setup of data science better than anyone.
  • Spotfire Data Science does a good job at making suggestions on modeling framework.
  • Spotfire Data Science is for the advanced user. A beginning analyst may find the capabilities of the software overwhelming.
  • Spotfire Data Science's default analytics models are not always the best.
Spotfire Data Science is world-class at building exploratory analyses and for creative analytical tasks. The software does these two things quite well. On the other hand, Spotfire Data Science is not well suited for creating real-time advanced analytical models that are used in a production environment. Other open-source models work better for such productions.
Score 9 out of 10
Vetted Review
Verified User
Incentivized
Data Science is used to figure out the fraud happening in our retail stores. It is used across our department and some other departments too. We usually use another UI application called Eagle to raise alerts for such doubtful transactions, and with Data Science, we can show the alerts and help business people prevent fraud.
  • It can handle huge data sets.
  • It can handle different data sources.
  • It is very quick in calculating things, as compared to almost any other tool.
  • Sometimes it crashes while developing the reports.
  • It should add some more charts like a donut, performance chart, etc.
  • It should be more consumer friendly in connecting to R.
It is well suited if you have large data sets to work on. It helps reports by caching the data so the consumers won't face any delay in opening the report. It also has the ability to use regression models to do predictive analysis, which makes Data Science unique from all other reporting tools.
Abigail Bowden | TrustRadius Reviewer
Score 8 out of 10
Vetted Review
Verified User
Incentivized
We use it to manage data collected during field work for environmental and geophysical purposes. We collect a lot of data with many aspects to it that is easy to mismanage. Spotfire Data Science has been incredibly helpful in organization, analysis, and management of collected data, as well as collaborating with coworkers on the data management and presentation for clients.
  • It has a great user interface, easy to navigate and learn on the fly.
  • There are lots of great options for data organization and analysis! Makes it a handy tool for presentations as well.
  • A collaborative ability is highly valued for my company where we often work from home or on site. Being able to share the data with those in the office so multiple people can look at it is a great tool!
  • The visualization aspect of the program can be a little tricky to figure out. It's great to have options but it will take a bit of practice before your figures start looking the way you want (or that's how it was for me).
  • While younger employees like myself may quickly grasp on to the program, the modern interface is difficult for older employees to navigate and get comfortable with. This isn't a problem until you are trying to collaborate with them and things go awry. Perhaps they just need in-depth tutorials to help expedite their learning process.
  • It can be difficult to connect to other databases to import existing data. It's just not an obvious pathway and required some researching before I got the hang of it.
It's well suited for companies who are working long-distance and who have lots of data to organize and present. My company does extensive field work collecting thousands of data points at a time, in many cases, so this is an excellent way to share data collected in the field with those still in the office so that reports can begin before our travels are really finished. It makes the office much more productive! Spotfire Data Science is less suited for companies with older employees or companies that are generally in one office and not doing distance work. It can be a little tricky for older people to grasp the interface and really utilize the program to its full potential so of course spending more time learning the software than using it effectively isn't a great use of time or money.
January 30, 2018

TIBCO Data Science

Score 8 out of 10
Vetted Review
Verified User
Incentivized
Our organization uses TIBCO Data Science mainly in our water quality and biological departments. We use this program to help with the massive data sets we produce. This software allows for us to create different ways to present that data.
  • Saves time by calculating things such as median value.
  • Easy to generate diagrams.
  • Easy to import data sets.
  • Saves time because you are able to choose what data you want to use and how you want to display it.
  • I’m still learning everything TIBCO has to offer.
  • My main focus has been mostly on box and our organization uses TIBCO Data Science mainly in our water quality and biological departments. We use this program to help with the massive data sets we produce. This software allows for us to create different ways to present that data.
  • I would like to get into more of the other options available.
If you are dealing with large datasets this product will be helpful. It will save you time and produce quicker results.
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.
Score 8 out of 10
Vetted Review
Verified User
Incentivized
Data Science is being used to compute data analysis models efficiently that would otherwise take longer than usual. It has a profound processor that it uses the right algorithms to achieve a dependable statistical value.
  • Data modeling
  • Analysis of stats
  • Performance features
  • User interface
  • Speed
It is very good for large piles of data that can be processed at one time and to make nice looking graphs for presentations.
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