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BEST DATA ANALYTICS TOOLS USED BY LEADERS
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The process of collecting and transforming data into meaningful insights may be challenging until you are familiar with good data analytical tools.
We are a technology consulting and software development company eager to share our knowledge and experience.
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So What are the Best Data Analysis Programs?
1. On top of the analytical pyramid we have Tableau, a leader in business intelligence and data analysis, according to Gartner.
2. Microsoft Power BI
Being able to connect to a large number of sources, this powerful tool puts your data into practice with live dashboards and reports.
3. QlikView
A self-service business intelligence platform where users can easily search, explore, and create dynamic apps to get business answers they need.
4. Apache Spark
This is a powerful product that provides dynamics and fast processing, real-time streaming, easy Hadoop integration, making it very suitable for data science projects.
5. Python.
It is a high-level programming language for general-purpose programming. It provides Python data analysis libraries that can be used almost for everything.
6. R
R is a software environment we majorly use for statistical analysis and graphics.
7. SAS.
We find it a prominent tool in the analytical market that enables better data analysis using SAS SQL and automatic code generation.
8. KNIME
is a free data solution for Windows, macOS, and Linux. Our team uses it to work with data from the ETL steps to analytics, including statistics and machine learning visualizations.
We are a technology consulting and software development company eager to share our knowledge and experience.
▶ USEFUL LINKS:
▶ TIME CODES:
▶ Follow us:
▶ About this video:
So What are the Best Data Analysis Programs?
1. On top of the analytical pyramid we have Tableau, a leader in business intelligence and data analysis, according to Gartner.
2. Microsoft Power BI
Being able to connect to a large number of sources, this powerful tool puts your data into practice with live dashboards and reports.
3. QlikView
A self-service business intelligence platform where users can easily search, explore, and create dynamic apps to get business answers they need.
4. Apache Spark
This is a powerful product that provides dynamics and fast processing, real-time streaming, easy Hadoop integration, making it very suitable for data science projects.
5. Python.
It is a high-level programming language for general-purpose programming. It provides Python data analysis libraries that can be used almost for everything.
6. R
R is a software environment we majorly use for statistical analysis and graphics.
7. SAS.
We find it a prominent tool in the analytical market that enables better data analysis using SAS SQL and automatic code generation.
8. KNIME
is a free data solution for Windows, macOS, and Linux. Our team uses it to work with data from the ETL steps to analytics, including statistics and machine learning visualizations.
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