Data Analytics Tools

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About the Program

There are numerous data analytics tools available, catering to various needs and preferences. These tools are used for tasks such as data cleaning, exploration, visualization, and statistical analysis.

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Here are some widely used data analytics tools

Microsoft Excel

Excel is a versatile spreadsheet tool widely used for basic data analysis and visualization. It's suitable for small to medium-sized datasets and is often used for tasks such as sorting, filtering, and creating charts.


Python is a powerful programming language with numerous libraries for data analytics, including:

  • Pandas: Data manipulation and analysis.
  • NumPy: Numerical computing and mathematical functions.
  • Matplotlib and Seaborn: Data visualization.
  • Scikit-learn: Machine learning.


R is a programming language specifically designed for statistical computing and graphics. It has a rich ecosystem of packages for data analysis and visualization, making it popular among statisticians and data scientists.


Tableau is a powerful data visualization tool that allows users to create interactive and shareable dashboards. It can connect to various data sources and is known for its user-friendly interface.

Power BI

Microsoft Power BI is a business analytics tool that enables users to visualize and share insights from their data. It integrates with various data sources and provides interactive dashboards and reports.

SQL (Structured Query Language)

SQL is a standard language for managing and manipulating relational databases. It's used for querying databases to retrieve, insert, update, and delete data. Popular relational database management systems (RDBMS) include MySQL, PostgreSQL, and Microsoft SQL Server.

Apache Hadoop

Hadoop is an open-source framework for distributed storage and processing of large datasets. It is commonly used for big data analytics and works well with tools like Apache Hive and Apache Pig for data processing.

SAS (Statistical Analysis System)

SAS is a software suite used for advanced analytics, business intelligence, and data management. It is widely used in industries such as finance, healthcare, and government.


KNIME (Konstanz Information Miner) is an open-source platform for data analytics, reporting, and integration. It allows users to visually create data flows, execute analyses, and deploy workflows.


Alteryx is a data blending and advanced data analytics tool that streamlines the process of preparing and analyzing data. It is known for its user-friendly interface and ability to handle complex data manipulation tasks.

Google Analytics

Google Analytics is a web analytics service that tracks and reports website traffic. It provides insights into user behavior, conversion data, custom reporting, and more.

Choosing the right tool depends on factors such as the specific requirements of the analysis, the size of the dataset, user proficiency, and organizational preferences. Many analysts and data scientists often use a combination of these tools based on the nature of the task at hand.

How to Apply

In order to pursue this program, the students can talk to our counceller or use links below for further details:

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