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The data science platforms now have become a very important tool for any enterprises who aspire to scale high on their frontiers. The data science platform essentially is the software hub over which all functionalities of data science like data integration and exploration from different coding, sources, and model building are done.
These platforms are well programmed to test and train models and deploy results to solve the real life problems. Let us look at the top 10 data science platforms, which are highly used and also liked by many businesses all over world. These are data science platforms, which feature most of Analytics code written!
Wolfram Mathematica
Wolfram’s Mathematica is the modern technical data computing application that features the flexible coding language and various data visualization and graphing capabilities. This is one powerful tool for the data computation and visualization. Solving mathematics especially calculus is easy.
MATLAB
MATLAB platform is highly used in the data analytics for machine learning, big data, statistics, neural networks, and cloud processing of the large data sets. Adaptability of the MATLAB ranges from advanced driver systems to telematics, predictive maintenance and sensor analytics. Users also can use this to access their data from various formats and sources including Hadoop distributed systems, data warehouses, IoT devices, spreadsheets, geospatial, audio, video, and web content among many more.
Alteryx Analytics
Alteryx is the computer software that offers predictive analytics and business intelligence products used for the data science and the analytics. This is the closed platform and costing differs from every user and year.
TIBCO Statistica
TIBCO Statistica is highly relied on by the business enterprises for solving any complex problems. This platform offers the users to create some innovative models with new deep learning, prescriptive, predictive, analytical and AI techniques. These platform’s capabilities will include comprehensive algorithms including clustering, regression, neural networks, decision trees, machine learning to be accessed through built-in nodes.
RapidMiner Studio
RapidMiner is the visual workflow creator for the data scientists that help them with the data preparation, deep learning, machine learning, predictive analytics and text mining. The repositories include library of more than 1500 machine learning functions and algorithms that help in building strongest predictive models used in any case.
Databricks Unified Analytics
Databricks Unified is developed from creators of the Apache Spark. The databricks workspace gives the users with the platform to manage analytic process from the ETL to deployment and model training through the shared notebooks, ecosystem integration and simplified production jobs.
Anaconda
With more than 6 million users all over the world, Anaconda is the open source and free distribution of the R programming and Python languages. The Anaconda products include Anaconda Enterprise and Anaconda Distribution.
Angoss KnowledgeSTUDIO
Angoss offers KnowledgeSTUDIO, which is billed as the simple to use predictive analytics and data mining platform. Angoss products are supported by the Datawatch.
R-Studio
RStudio is the free and the open source analysis development environment for R community. With the built-in packages, it is one interactive platform for the statistical computing & graphics. Highly adaptive platform generally runs on all Windows and Mac or Linux desktops. While
H2O
H2O is the data science & machine learning platform that is used by more than 14,000 organizations & 155,000 users all over the world across Healthcare, Finance, Telco, Retail, Manufacturing industry. This platform’s open source comprise of H2O, referred as the top machine learning platforms
KNIME Analytics Platform
KNIME Platform is the open source software, which builds data science workflows only for the advanced predictive and machine learning algorithms. The platform is totally based on the drag and drop type of graphical interface, which helps the users to create the visual workflows just by scripting in R and Python data from the multiple sources of CSV, XLS, JSON, PDF, XML, or from the unstructured data sources images and documents.
Microsoft R
Rev-R solves the Big Data gap just by allowing the scientists to load huge data in the Hadoop HDFS & run complex algorithms like decision trees and Random Forest by running algorithms in the distributed way on cluster.
Cloudera Data Science Workbench
This platform suits the needs of the data scientists & IT Professionals. The scientists can experiment it with latest libraries & frameworks scripting on Python, R, and Scala programming language and with secure access to the Apache Spark™ & Apache Impala™.