About Top 10 Data Science Platforms that Cash Analytics Code

Data science is the study of data. By using this field you can develop the methods of recording and able to store and analyze data to extract valuable and effective information.

The valuable information provided by data science helps in understanding complex or large data. It is an amalgamation of work of different fields that combines all these works in statistics and computation to illustrate data. This interpretation of data helps in making decisions for various purposes.

Data science platforms are used for enhancing business outcomes and improving customer experience. These data platforms are flexible and assist data science teams to bring out the best output from data.

Importance of Data Science Platforms

A data science platform is an essential tool for coding, model building and solving real-life problems. These tools are as important for big businesses as small enterprises to scale up their frontiers. 

User or developers can use these data science platforms as a software hub and for data mining, data organizing, data exploring, coding, model building as well as to perform other functioning applications

Top 10 Data Science Platforms

In this article, we are going to learn about 10 data science platforms which are the favorite ones to most of the organization and business. For various business operations in the IT & corporate world, these platforms are widely used. Let’s look at the platforms which are discussing down below.

Cloudera Data Science Workbench

Most of the data scientists and IT professionals choose this data science platform as it fulfills their basic needs. Users can experiment with this platform with the latest libraries. Developers use it for frameworks scripting on python, R and Scala programming language. With its security developer can access to Apache Spark and Apache Impala.

KNIME Analytics Platform

For the latest machine learning algorithms, this data science platform is the best choice. This open-source software can form data science workflows. Users can find drag and drop graphical interface in this platform. From unstructured data sources and from other sources a user can script in R and Python data and create the visual workflows.

Microsoft R

With the help of this data science, platform developers can load large data in the Hadoop HDFS. To solve big data gap Microsoft R is the right platform which runs complex algorithms in the distributed way on the cluster.

R-Studio

R-studio is based on built-in packages and used for statistical computing and graphics. This open-source platform analysis development for R community. For its high adaption quality, this platform can on all windows versions as well as Mac or Linux desktops. Walmart, Samsung, eBay, Accenture, Honda, NASA, Western Union, all these big business names are the users of R-studio.

H2O

Users can use this open-source platform for getting top machine learning experience. Almost all organizations and users from all over the world use this data science platform. Users can find H2O is the open-source of this platform.Finance, retail, manufacturing industries all use this data science platform for development.

The enterprise of this platform offers an automatic machine learning platform -Driverless AI-for the use of business enterprises. The platforms of H2O are used by Cisco, Macy’s, Capital One, Paypal, Dun & Bradstreet and many more.

Anaconda

Developers use Anaconda for the free distribution of the R programming and Python languages. If you overview of this open-source platform you can see almost 6 million users around the world use this platform. Anaconda Enterprise and Anaconda Distribution are among the best products of Anaconda.

By using these platform business enterprises can add and increase the capabilities of data science, machine learning and artificial intelligence with the development, training, and deployment of model.

Anaconda is used for reducing the costs of maintenance and improving the safety and credibility of the electric transmission assets by National Grid which is a British MNC electricity and gas utility company.

Databricks Unified Analytics

The inventors of Apache Spark creates this data science platform. By using this platform user can manage the analytic process from ETL to expansion and model training via the shared notebooks, ecosystem integration and simplified production jobs.

Alteryx Analytics

By using predictive analytics and business intelligence products, this computer software platform analyses data. These products are best for use in data science and analytics. The cost of this product depends on its use and changes from time to time. Many popular names use this platform and help it to grow. These names include Audi, Hyatt, Unilever. Johnson & Johnson and many more.

Angoss Knowledge Studio

Angoss offers a knowledge studio. Developers can use it for predictive analytics and data mining platform. The best part of this platform is that Angoss pays full attention to every model development. Datawatch supports all the products of Angoss.

MATLAB

Mostly for data analytics like machine learning, neural networks, statistics, big data and cloud processing of huge datasets set, this platform is highly recommended by the developers. MATLAB is capable of adapting advanced systems to telematics, predictive maintenance, and sensor analytics. 

Users can use this data science platform for accessing your data from several platforms. These platforms include data warehouse, spreadsheets, Hadoop distributed systems, web content, geospatial, audio, video and others.

Concluding Notes

All these data science platforms have advanced features and written analytics code. Because you can find several data visualization and graphing potentialities in them, these platforms have become important tools for aspiring high scale for most of the enterprises.