Top 10 Data Science Tools in 2019 to Eliminate Programming

Explore the Best Data Science Tools Available in the Market:

Data Science includes obtaining the value from data. It is all about understanding the data and processing it to extract the value out of it.

Data Scientists are the data professionals who can organize and analyze the huge amount of data.

The functions that data scientists perform include identifying relevant questions, collecting data from different data sources, data organization, transforming data to the solution, and communicating these findings for better business decisions.

Data Science Tools

Python and R are the most popular languages among data scientists. The image given below will show you the popularity graph of these two languages.

Popularity Graph of Data Science

Refer the below image to understand the Data Science Life Cycle.

Data Science Life Cycle

[image source]

Data science tools can be of two types. One for those who have programming knowledge and another for the business users. Tools which are for business users, automate the analysis.

Classification of Data Science Software:

Tools for those who don’t have programming knowledgeTools for programmers
Rapid MinerPython
Data RobotR
TrifactaSOL
IBM Watson StudioTableau
Amazon LexTensorFlow
NoSQL
Hadoop

******************
=>> Contact us to suggest your listing here.
******************

List of The Top Data Science Software Tools

Let's explore the top tools that data scientists use. Ranking of paid and free tools based on popularity and performance. 

#1) RapidMiner

Price: A free trial is available for 30 days. RapidMiner Studio price starts at $2500 per user/month. RapidMiner Server price starts at $15000 per year. RapidMiner Radoop is free for a single user. Its enterprise plan is for $15000 per year.

Rapid Miner

RapidMiner is a tool for the complete life-cycle of prediction modeling. It has all the functionalities for data preparation, model building, validation, and deployment. It provides a GUI to connect the predefined blocks.

Features:

  • RapidMiner Studio is for data preparation, visualization, and statistical modeling.
  • RapidMiner Server provides central repositories.
  • RapidMiner Radoop is for implementing big-data analytics functionalities.
  • RapidMiner Cloud is a cloud-based repository.

Website: RapidMiner

#2) Data Robot

Price: Contact the company for detailed pricing information.

Data Robot

Data Robot is the platform for automated machine learning. It can be used by data scientists, executives, software engineers, and IT professionals.

Features:

  • It provides an easy deployment process.
  • It has a Python SDK and APIs.
  • It allows parallel processing.
  • Model Optimization.

Website: Data Robot

#3) Apache Hadoop

Price: It is available for free.

Apache Hadoop

Apache Hadoop is an open source framework. Simple programming models that are created using Apache Hadoop, can perform distributed processing of large data sets across computer clusters.

Features:

  • It is a scalable platform.
  • Failures can be detected and handled at the application layer.
  • It has many modules like Hadoop Common, HDFS, Hadoop Map Reduce, Hadoop Ozone, and Hadoop YARN.

Website: Apache Hadoop

#4) Trifacta

Price: Trifacta has three pricing plans, i.e. Wrangler, Wrangler Pro, and Wrangler Enterprise. For the Wrangler plan, you can sign up for free. You will have to contact the company to know more about the pricing details of the other two plans.

Trifacta

Trifacta provides three products for data wrangling and data preparation. It can be used by individuals, teams, and organizations.

Features:

  • Trifacta Wrangler will help you in exploring, transforming, cleaning, and joining the desktop files together.
  • Trifacta Wrangler Pro is an advanced self-service platform for data preparation.
  • Trifacta Wrangler Enterprise is for empowering the analyst team.

Website: Trifacta

#5) Alteryx

Price: Alteryx Designer is available for $5195 per user per year. Alteryx Server is for $58500 per year. For both the plans, additional capabilities are available at an additional cost.

Alteryx

Alteryx provides a platform to discover, prep, and analyze the data. It will also help you to find deeper insights by deploying and sharing the analytics at scale.

Features:

  • It provides the features to discover the data and collaborate across the organization.
  • It has functionalities to prepare and analyze the model.
  • The platform will allow you to centrally manage users, workflows, and data assets.
  • It will allow you to embed R, Python, and Alteryx models into your processes.

Website: Alteryx Designer

#6) KNIME

Price: It is available for free.

KNIME

KNIME for data scientists will help them in blending tools and data types. It is an open source platform. It will allow you to use the tools of your choice and expand them with additional capabilities.

Features:

  • It is very useful for the repetitive and time-consuming aspects.
  • Experiments and expands to Apache Spark and Big data.
  • It can work with many data sources and different types of platforms.

Website: KNIME

#7) Excel

Price: Office 365 for personal use: $69.99 per year, Office 365 Home: $99.99 per year, Office Home & Student: $149.99 per year. Office 365 Business is for $8.25 per user per month. Office 365 Business Premium is at $ 12.50 per user per month. Office 365 Business Essentials is at $5 per user per month.

Excel

Excel can be used as a tool for data science. It is easy to use tool for non-technical persons. It is good for analyzing data.

Features:

  • It has good features for organizing and summarizing the data.
  • It will allow you to sort and filter the data.
  • It has conditional formatting features.

Website: Excel

#8) Matlab

Price: Matlab for an individual user is at $2150 for a perpetual license & $860 for an annual license. A free trial is available for this plan. It is also available for Students as well as for personal use.

Matlab

Matlab provides you the solution for analyzing data, developing algorithms, and for creating models. It can be used for data analytics and wireless communications.

Features:

  • Matlab has interactive apps which will show you the working of different algorithms on your data.
  • It has the ability to scale.
  • Matlab algorithms can be directly converted to C/C++, HDL, and CUDA code.

Website: Matlab

#9) Java

Price: Free

Java

Java is an object-oriented programming language. The compiled Java code can be run on any Java supported platform without recompiling it. Java is simple, object-oriented, architecture-neutral, platform-independent, portable, multi-threaded, and secure.

Features:

As features, we will see why Java is used for data science:

  • Java provides a good number of tools and libraries that are useful for machine learning and data science.
  • Java 8 with Lambdas: With this, You can develop large data science projects.
  • Scala provides the support to data science.

Website: Java

#10) Python

Price: Free

Python

Python is a high-level programming language and provides a large standard library. It has the features of object-oriented, functional, procedural, dynamic type, and automatic memory management.

Features:

  • It is used by data scientists as it provides a good number of useful packages to download for free.
  • Python is extensible.
  • It provides free data analysis libraries.

Website: Python

Additional Data Science Tools

#11) R

R is a programming language and can be used on a UNIX platform, Windows, and Mac OS.

Website: R Programming

#12) SQL

This domain-specific language is used for managing the data from RDBMS through programming.

#13) Tableau

Tableau can be used by individuals as well as teams and organizations. It can work with any database. It is easy to use because of its drag-and-drop functionality.

Website: Tableau

#14) Cloud DataFlow

 Cloud DataFlow is for stream and batch processing of data. It is a fully-managed service. It can transform and enrich the data in the stream and batch mode.

Website:  Cloud DataFlow

#15) Kubernetes

Kubernetes provides an open source tool. It is used to automate the deployment, scale, and manage containerized applications.

Website: Kubernetes

Conclusion

RapidMiner is good for extracting the value out of your data and for creating models. Data Robot provides a platform to become an AI-driven enterprise. It is best for predictive analytics.

Trifacta can work with complex data formats like JSON, Avro, ORC, and Parquet. Apache Hadoop is best as an open source software library for working with large datasets.

KNIME is a free and open source platform for blending tools and data types. Excel is easy to use for non-technical users. Python is popular among the data scientists because of its libraries.

Java is used by many organizations for enterprise development. Hence, models written in R & Python can be written in Java to match up with the organization’s infrastructure.

Hope you enjoyed this informative article on Data Science Tools.

******************
=>> Contact us to suggest your listing here.
******************