Top 10 Data Science Platforms that Cash the Analytics Code

Data science platforms are necessary tools for any enterprise who aspire to scale it’s business further. Data science platform is a software hub where all the data science functionalities such as data integration and exploration from various model building, sources and coding are done.

Data science platforms are helping enterprises in scaling their profits and revenues, which can be proved by the fact that global data science platform is expected to grow at a CAGR of around 22.7% to reach to $6.06 billion by 2023.

Selecting a data science platform among several open and closed platforms can be a difficult task; however, every organization has different requirements, and they must choose only those platforms which accurately fulfill their needs.

In a recent study, it was found that 62% of the data science professionals would select open source languages such as R and Python over legacy solution SAS.

Here are some of the best data science platforms that cash the analytics code and are widely used businesses across the globe:

1. Alteryx Analytics

Alteryx Analytics provides analytics and intelligence products and for data science. It is a closed platform with its headquarters in California.

Their price starts at $3,995 per year subscription. Their cloud-based analytics gallery cost around $1,950 per year. Alteryx Analytics co-partners include Microsoft, Qlik, Tableau and Amazon Web Services.


The MATLAB is an extremely user-friendly platform which is used in data analytics for neural networks, cloud processing, machine learning, etc.

It is highly adaptive and ranges from sensor analytics, telematics, to predictive maintenance. Anyone using MATLAB can access information and data from various sources and formats such as IoT devices, web content, file systems, video, audio and many more.

Its individual annual licenses pricing starts from $820 per year. It also offers 1-month free trial.

3. RapidMiner Studio

RapidMiner helps the data scientists with machine learning, predictive analytics, preparation of data, and mining of texts.

Its library contains more than two thousand machine learning functions and algorithms which helps in creating the best predictive model for any case.

It easily integrates with most of the tools and languages such as Python and R. It also has a tool RapidMiner Turbo Prep which is used by users as well as data scientists to pivot and change data from one source to the other.

  1. TIBCO Statistica

TIBCO Statistica is used by many enterprises to solve their complex issues. In this platform, users can build their creative models with updated analytical techniques, learning, AI and others.

TIBCO Statistica can create complex analytics algorithms including neural networks, clustering, machine learning, which can be accessed through several nodes.

Many analytic workflow templates are available for users along with open source scripts such as Python, Scala, C#.

5. Anaconda

Anaconda is an open source and free platform with over seven million users all over the world. Their most popular products include Anaconda Enterprise and Anaconda Distribution.

Its enterprise version helps businesses to use artificial intelligence, data science capabilities through model training and development.

On the other hand, Anaconda Distribution allows users to manage the environment and platform for 2,000 data packages for Python for Data Science and R programming language.

Anaconda is extensively used many renowned organizations including the British gas and electricity company National Grid to improve safety and reduce overall costs.

6. Databricks Unified Analytics Platform

The founders of Apache Spark created Databricks Unified Analytics Platform.

It is a platform where users can manage all of their analytics processes through shared notebooks and integrating the ecosystem.

Users can train their AI applications and models on a real-time basis. It is available for a two-week free trial.

7. KNIME Analytics Platform

KNIME Analytics Platform is used for advanced analytics and machine learning algorithms by building end to end data science workflows.

Users can create visual workflows through a drag and drop style tool which is scripted in R and Python data from several sources like CSV, XML, PDF, XLS or through unstructured sources including documents and images.

Users can quickly retrieve their data from Twitter, Google Sheets, Amazon Web Services and many more.

  1. H2O

H2O is a well-known machine learning and data science platform which is used by more than two lakhs users in over twenty thousand organizations across the globe.

Its tool Driverless AI was included in the list of 2018 InfoWorld Technology Awards winners.

Their open source offering includes H2O and Sparkling Water which is an open source integration with NVIDIA GPU, Spark, and H2O4GPU.

H2O is a popular platform in several big multi-million dollar companies such as PayPal, Cisco, Dun & Bradstreet, and several manufacturing industries.

9. Cloudera Data Science Workbench

Cloudera Data Science Workbench is one of the most favorite platforms of data scientists, software experts, and programmers.

Users and data scientists can use the latest and updated frameworks and libraries which are scripted on Scala, R and Python programming language.Users can build and train their machine learning models with just a few clicks and drags which is more flexible as compared to the other platforms.

  1. R-Studio

R-Studio is an IDE (integrated development environment) which can be mostly used for R programming language users.

Its platform is very interactive, and it also contains built-in packages for statistical computing and graphics.

The platform can efficiently run on Mac, Linux as well as Windows desktops and laptops.
Although R-Studio is free, its commercial license costs around $1000 per year which provides email and call support.

Most of the big brands and companies such as Honda, eBay, Walmart, Accenture, Western Union, Samsung, NASA use this platform.

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About the Author: Randy Smith

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