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Data Analytics Tools

Data Analytics Tools

In the current global economy, Data Analytics is becoming one of the fast-growing jobs worldwide. According to development, these are many different tools for data analysis. Each of them has different strengths. Today, JT1 will introduce you to some Data Analytics Tools.

Data Analytics Tools

Top best Data Analytics Tools:

1. Tableau Public:

Tableau is a quick, simple and intuitive tool for everyone. It is particularly powerful by conveying information through visual data. Tableau Public offers free trials to individuals or organizations before upgrading to advanced applications. During the analysis process, Tableau’s visuals allow you to check the hypothesis, discover general data before embarking on data mining.

Some advantages of Looker:

  • It has a free version.

  • It has interacted with any data from excel, Data Warehouse to Websites.

  • Abilities to update data according to real-time.

  • Make data intuitive in many ways such as Charts or even a Dashboard which seem better than any other software on the market.

  • Tableau's Big Data processing system is very powerful.

2. OpenRefine:

OpenRefine is a data cleansing software that helps you get everything ready for analysis. We can use OpenRefine to filter content, edit information simultaneously on multiple data streams at the same time. Besides, OpenRefine also a program is run on Java-based programs: This is a computer application that uses your website browser and works on a graphical interface.

Some advantages of Looker:

  • It helps to solve inconsistencies in the dataset.

  • It also helps to split data into several small parts.

  • Match local data with other data sets

  • Save a set of steps as data for playback on the same file

  • Enhance datasets with data from many other sources.

  • Overview and data synchronization.

3. Orange:

Orange for data is a tool that uses open source. It helps to synthesize and bring data visualizations. Furthermore, Orange also has some advantages including:

  • Perform data analysis: Turn raw data into simplified data.

  • Create many beautiful and comfortable template tables.

  • Get sources from multiple sources for advanced analysis.

4. RapidMiner:

RapidMiner is an open-source that is applied to Machine learning and Data mining environment, besides it also uses Java programming language. Moreover, RapidMiner not only is used under the Client/Server model with an on-premise or public cloud / private cloud server but also is applied on working because of convenience, easy to use, regardless of the Output, but also can create a template according to the Label or Target tag.

Some important notes about RapidMiner:

  • Download and automatically convert data

  • Data processing and visualization

  • Develop forecasting models and detailed statistical analysis

  • Evaluate and deploy data

5. Excel:

Excel is known as a part of the Microsoft Office office toolkit including many software that supports to write documents, presentations, email management,... This software helps create spreadsheets, along with features and tools that help users calculate data quickly and accurately with millions of cells.

Some important notes about RapidMiner:

  • There are advanced analytics features that help to model data such as automated relational settings, DAX solutions, and time groups.

  • Used in data analysis in all industries.


KNIME is known as specialized software that provides analysis, data mining and works for an organization in a certain structure according to professional interface and visualization. KNIME supports more than 1000 modules and the ability to handle multiple types of data such as XML, JSON, picture, document,... Besides, KNIME also supports synthetic data and presents an analysis in the form of tables, graphs, and maps.

Some advantages of KNIME:

  • Analyze and automatically extract data with one mouse click

  • Organize work according to the available structure.

  • Processing many types of XML, JSON,...

  • Change the properties of nodes.

  • Exploiting AI algorithms and prediction algorithms in a professional way.

7. Python:

Python is a popular scripting programming language. It is suitable for people who start to learn programming language. It also is believed by many corporations such as Microsoft, Google, the IT company because it is easy to learn and easy to understand.

Some advantages of Python:

  • It is many people evaluated as easy to learn, to write, to maintain, also provided under types Open Source (free).

  • Besides, Python also has a good library such as Theano, Keras, Tensorflow,...

  • Ability to collect on multiple platforms such as SQL Server, MongoDB, JSON files.

8. SAS:

This is one of the specialized programs for serving and analyzing statistics very popular in the world. It allows users to manipulate data in almost every way possible. SAS also introduces Proc SQL procedure which allows performing every questions SQL on the data file.

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Some advantages of SAS:

  • It is a good environment for programming and Data manipulation in data analysis.

  • It is easy to connect, manage and analyze figures data from any source.

  • It includes many modules for web, social network, and marketing analysis that are widely used to profile leads.

  • Able to predict behavior, manage and optimize communication.

9. Looker:

This is a data analysis application that provides manage data functions for F&B enterprise. When using this tool, the user can access it directly on the web easily to receive detailed information and real-time about their activities through data analysis. Furthermore, Looker also all companies use and analyze data to make a decision about suitable business activities.

Some advantages of Looker:

  • It is easy to build and create dashboard on any devices

  • Increase interactive features.

  • Fully customizable reports, graphs and graphs, and export

  • Connect directly with any SQL data Connect on any platform.

  • Discover and connect data through real-time.

10. R Programming:

R Programming is a platform-independent, so we can use it for any operating system. The installation of this tool is also free, so we can use it without having to buy a license.

Some advantages of R Programming:

  • It is a leading tool in analytics, widely used in Data modeling.

  • Manipulations on R Programming is easy.

  • Using SAS about Data Capacity.

  • Running on multiple platforms such as UNIX, macOS, and Windows.

  • More than 11.556 packages can be installed automatically according to user demands.

Data Analytics

With some information about Data Analytics Tools which provide you. We hope that you will more understand about Data Analytics Tools.

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