Top Data Science Tools in Demand

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Top Data Science Tools in Demand
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1. Apache Hadoop
An open-source framework for storing and
processing massive data sets on clusters of
computers used in big data applications.
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2. Tableau
A data visualization tool used for interactive,
easy-to-understand data analysis.
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3. Jupyter Notebook
An open-source web-based tool for creating and
sharing documents that combine live code,
equations, visualizations, and narrative text.
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4. Matlab
A powerful tool for data science, providing
various built-in functions and toolboxes for
data analysis, visualization, and modeling.
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5. KNIME
An open-source data analytics and machine
learning platform that allows users to create
and execute workflows on diverse data sources.
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6. Google Analytics
A web analytics tool that tracks and analyses
website traffic and user behavior to improve
online performance and user experience.
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7. Python
A popular data science programming language due
to its simplicity, versatility, and large
libraries for analysis, visualization, and
machine learning.
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8. R (RStudio)
An integrated development environment for the
programming language R, used for data analysis,
visualization, and machine learning.
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9. Excel
A spreadsheet tool for organizing, analyzing,
and visualizing data with functions, formulas,
and pivot tables.
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10. Statistical Analysis System (SAS)
A powerful statistical analysis software tool
used for data management, advanced analytics,
and business intelligence.
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11. SQL
A powerful data science tool for managing and
analyzing structured data using queries and
relational databases.
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12. PowerBI
A data visualization and business intelligence
tool used to analyze and present data insights.
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13. Spyder
A user-friendly open-source integrated de-
velopment environment for data science with
interactive plotting, debugging, and code
editing capabilities.
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