Data Science Platforms

Data Science Platforms Overview

Data science technology can help organizations turn their data into a valuable resource in the creation of business value. Data science tools are capable of handling data volumes that are too big for traditional databases or statistical tools.


Data science tools create value by mining large amounts of structured and unstructured data to identify patterns can help an organization to more effectively manage costs and achieve competitive advantage.


Data science tools incorporate a variety of component technologies such as machine learning, data mining, data modeling, data mining, and visualization.

Top Rated Data Science Products

TrustRadius Top Rated for 2021

These products won a Top Rated award for having excellent customer satisfaction ratings. The list is based purely on reviews; there is no paid placement, and analyst opinions do not influence the rankings. Read more about the Top Rated criteria.

Data Science Platforms TrustMap

TrustMaps are two-dimensional charts that compare products based on trScore and research frequency by prospective buyers. Products must have 10 or more ratings to appear on this TrustMap.

Data Science Products

(1-25 of 47) Sorted by Most Reviews

The list of products below is based purely on reviews (sorted from most to least). There is no paid placement and analyst opinions do not influence their rankings. Here is our Promise to Buyers to ensure information on our site is reliable, useful, and worthy of your trust.
RStudio

RStudio

Customer Verified
Top Rated

RStudio is a modular data science platform, combining open source and commercial products. The vendor states their open source offerings, such as the RStudio IDE, Shiny, rmarkdown and the many packages in the tidyverse, are used by millions of data scientists around the world to…

Key Features

  • Visualization (11)
    88%
    8.8
  • Extend Existing Data Sources (11)
    80%
    8.0
  • Automatic Data Format Detection (11)
    74%
    7.4
Alteryx

Alteryx

Customer Verified

Alteryx aims to be the launchpad for automation breakthroughs. Be it for personal growth, achieving transformative digital outcomes, or rapid innovation, the vendor boasts users will see unparalleled results. Alteryx converges analytics, data science and process automation into one…

Key Features

  • Integration with R or other statistical packages (42)
    88%
    8.8
  • Drill-down analysis (43)
    83%
    8.3
  • Formatting capabilities (48)
    75%
    7.5
IBM Watson Studio on Cloud Pak for Data

IBM Watson Studio enables users to build, run and manage AI models, and optimize decisions at scale across any cloud. IBM Watson Studio enables users can operationalize AI anywhere as part of IBM Cloud Pak® for Data, the IBM data and AI platform. The vendor states the solution simplifies…

Key Features

  • Visualization (21)
    78%
    7.8
  • Connect to Multiple Data Sources (21)
    78%
    7.8
  • Extend Existing Data Sources (21)
    75%
    7.5
MATLAB

MATLAB

Customer Verified
Top Rated

MatLab is a predictive analytics and computing platform based on a proprietary programming language. MatLab is used across industry and academia.

Anaconda

Anaconda

Customer Verified
Top Rated

Anaconda is an open source Python distribution / data discovery & analytics platform.

Key Features

  • Data Transformations (27)
    88%
    8.8
  • Extend Existing Data Sources (25)
    86%
    8.6
  • Visualization (26)
    86%
    8.6
Jupyter Notebook

Jupyter Notebook

Customer Verified
Top Rated

Jupyter Notebook is an open-source web application that allows users to create and share documents containing live code, equations, visualizations and narrative text. Uses include: data cleaning and transformation, numerical simulation, statistical modeling, data visualization, and…

Key Features

  • Visualization (24)
    92%
    9.2
  • Interactive Data Analysis (24)
    90%
    9.0
  • Connect to Multiple Data Sources (24)
    85%
    8.5
DataRobot

The DataRobot AI Cloud platform is presented as a solution that accelerates and democratizes data science by automating the end-to-end journey from data to value and allows users to deploy AI applications at scale. DataRobot provides a centrally governed platform that gives users…

Key Features

  • Interactive Data Analysis (18)
    82%
    8.2
  • Visualization (18)
    82%
    8.2
  • Automatic Data Format Detection (18)
    75%
    7.5
RapidMiner Studio

RapidMiner Studio is a data science and data mining platform from RapidMiner in Cambridge, Massachusetts.

TIBCO Data Science (including Team Studio and Statistica)

TIBCO® Data Science is presented by the vendor as 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…

Databricks Lakehouse Platform (Unified  Analytics Platform)

Databricks in San Francisco offers the Databricks Lakehouse Platform (formerly the Unified Analytics Platform), a data science platform and Apache Spark cluster manager. The Databricks Unified Data Service aims to provide a reliable and scalable platform for data pipelines, data…

KNIME Analytics Platform

Swiss company KNIME offers their KNIME Analytics Platform for big data and predictive analytics.

OpenText Magellan

OpenText Magellan Analytics Suite leverages a comprehensive set of data analytics software to identify patterns, relationships and trends through data visualizations and interactive dashboards.

IBM Streaming Analytics

IBM Streaming Analytics is a fully managed service that frees you from time-consuming installation, administration, and management tasks, giving you more time to develop streaming applications. It is powered by IBM Streams, an advanced analytic platform that you can use to ingest,…

Oracle Machine Learning (formerly Oracle Advanced Analytics)

Oracle Machine Learning (formerly Oracle Advanced Analytics) combines the Oracle database with Oracle Data Miner and SQL as well as R programming language functionality, providing a complete predictive analytics suite.

Wolfram Mathematica

Wolfram's flagship product Mathematica is a modern technical computing application featuring a flexible symbolic coding language and a wide array of graphing and data visualization capabilities.

Mode Analytics

Mode is an analytics platform designed to help data analysts and data scientists analyze, visualize, and share data, from Mode Analytics headquartered in San Francisco. The Studio support level provides individual analysts or up to 5 users with an SQL editor, as well as a Python…

Microsoft R Open / Revolution R Enterprise

Microsoft R Open and Revolution R Enterprise are big data R distribution for servers, Hadoop clusters, and data warehouses. Microsoft acquired original developer Revolution Analytics in 2016. Microsoft R is available in two editions: Microsoft R Open (formerly Revolution R Open)…

SAS Enterprise Miner

SAS Enterprise Miner is a data science and statistical modeling solution enabling the creation of predictive and descriptive models on very large data sources across the organization.

Dataiku DSS

Dataiku is a French startup and its product, DSS, is a challenger to market incumbents and features some visual tools to assist in building workflows.

Azure Data Science Virtual Machines (DSVM)

Available on Microsoft's Azure platform, Data Science Virtual Machines (DSVMs) are comprehensive pre-configured virtual machines for data science modelling, development and deployment.

H2O

H2O.ai is an open-source predictive analytics and machine learning platform.

Cloudera Data Science Workbench

Cloudera Data Science Workbench enables secure self-service data science for the enterprise. It is a collaborative environment where developers can work with a variety of libraries and frameworks.

SAP Predictive Analytics

SAP Predictive Analytics is, as the name would suggest, a statistical analysis and data mining platform that can be deployed with SAP HANA.

NVIDIA RAPIDS

NVIDIA RAPIDS is an open source software library for data science and analytics performed across GPUs.

Iguazio

Iguazio, headquartered in Herzliya, provides a Data Science Platform to automate machine learning pipelines. It aims to accelerate the development, deployment and management of AI applications at scale, enabling data scientists to focus on delivering better, more accurate and more…

Learn More About Data Science Platforms

What is Data Science Software?

Data science technology can help organizations turn their data into a valuable resource in the creation of business value. Data science tools are capable of handling data volumes that are too big for traditional databases or statistical tools.


Data science tools create value by mining large amounts of structured and unstructured data to identify patterns can help an organization to more effectively manage costs and achieve competitive advantage.


Data science tools incorporate a variety of component technologies such as machine learning, data mining, data modeling, data mining, and visualization.

Why did Data Science Technology Emerge?

Data science is an emerging response to the unprecedented volumes of data that are available to businesses for decision-making purposes. The desire to derive social and economic value from this newly available data is limited only by the lack of expertise and tools. Data science tools have emerged to fill this gap.

Data Science Software Features & Capabilities

Data Science platform features vary considerably from one product to the next. Available features also differ between features for bona fide data science platforms and machine learning tools which are really a subset of data science.


  • Data access and ingestion

  • Data preparation

  • Data visualization and discovery

  • Advanced modeling

  • Model deployment

  • Integration with big data tools like Hadoop

  • Access control

  • Audit logs

  • Reports

What Skills are Required?

The skill sets required for true data science are in short supply. This puts pressure on tool developers to reduce complexity to increase the potential user pool. In general, data scientists have advanced analytics skills like actuaries, who calculate insurance risks and premiums. They are quantitative researchers who typically have strong programming skills.

What do Data Scientists Do?

Although data scientists write code, they are quite different to developers. One of the main differences is that data scientists are primarily engaged in research, rather than in building products.


The job performed by data scientists is largely experimental. They build models that are designed to be predictive and then run them to see how well they perform. Then they tweak them and run them again.


The kinds of problems data scientists try to solve use huge amounts of unstructured data. Some examples are models that accurately predict customer churn or models to optimize vacation rental pricing based on location, time of year, etc.

Collaboration with Business

Agile development processes require a user or client to articulate the business need and provide constant feedback on what is being built. Data science teams are similar. They are most effective when they work closely with the people who actually use the models that they build. Without this alignment, the models built may not effectively solve the business problem that the business unit is struggling with.

Types of Data Science Platforms

Some platforms are primarily about model development and contain coding language capabilities to this end. Data Science models are typically quite complex and require advanced coding skills and often specialized hardware. Data scientists also frequently utilize many machines concurrently by spreading work across them.


A number of platforms do not contain languages for writing code but, instead, allow products like R, SAS, or Python to execute model code. Instead, they function as a system of record for all the models being developed by an entire data science team.

Pricing Information

Data scientists use a wide variety of tools some of which, like Python and Apache Spark and Hadoop, are open-source. Data scientists also use data mining tools, NoSQL databases, statistical computing tools like R, and others.


Enterprise data science platforms that keep track of projects and automate some of the code writing are relatively new arrivals. These platforms charge for an annual subscription. The price can vary depending on whether the software is running in the cloud or on-premise. There are also likely to be usage fees for compute time.