Nowadays many data scientists and data analysts rely on Tableau vs Python for data analysis and data visualization. But which one of them is better than the other and can provide more benefits to a data scientist or data analyst? These are the questions that we are about to answer today via this post. So, today we are going to compare both Tableau and Python to find out which of them is better than the other for data science and provide more benefits to its users.
Tableau is a great and robust business intelligence and data visualization tool. The main reason behind the popularity of this tool is its data handling and data visualization capabilities. It helps data scientists transform raw data into insights and present them via visual dashboards and worksheets. It is mainly a visual analytics framework that can easily change the way organizations use data. To learn more about this great visual analytics framework, feel free to join the Tableau Online Training in Saudi Arabia.
Python on the other hand is a very powerful high-level programing language that is mainly used for developing/creating robust web apps, software, data analysis, etc. The main reason behind the popularity of this programing language is it’s easy to learn and use syntaxes that make the work of its users very easy. Besides this, it contains various data science packages and deep learning frameworks that make the work of data analysts or scientists very easy.
Tableau is a data visualization tool and helps its users easily interpret data and discover meaningful business insights. It allows its users to easily understand the link or relation between databases. Besides this, it can easily work with a large volume of data.
Whereas pythons are mainly used to develop programs that can solve computer and business problems. It contains various packages and libraries that allow its users to develop robust and highly scalable programs in a very short time. Besides this, it also contains various data science packages and deep learning frameworks that make the work of data analysts or scientists very easy.
Tableau comes with lots of great features and powerful data handling capabilities. It can easily work with large datasets from multiple data sources. Besides this, it can easily load and work with different data types like text files, JSON, CSV, etc. You can also connect it with other databases using the ODBC connector.
Python comes with powerful data handling capabilities and is perfect for data streaming. Besides this, it has a very big user community and if you face any problem with it while working with your data you can easily find a package to solve that problem. Furthermore, it contains lots of libraries that allow its users to indirectly load and work with various data types.
Tableau is a great visual analytics framework and comes with robust data visualization capabilities. The framework comes with easy to use drag and drop tool that allows its users to easily develop quality data visualizations without any difficulty. Furthermore, it is very user-friendly too. To learn how to create data visualizations using this great visual analytics framework feel free to join the Tableau Online Training in Kuwait.
On the other hand, you can use Python for data analytics and data visualization. The programming language comes with libraries like MatPlotLib, SeaBorn, ggPlot, etc. that allow users to create appealing data visualizations using their datasets. However, it does not come with robust data visualization capabilities, and creating data visualizations using it is a very complex and time-consuming task.
Both Python and Tableau come with lots of phenomenal features that provide lots of advantages and benefits to data scientists and analysts. But both of them are also very different from each other and have their pros and cons. However, Tableau appears to be a better option than Python for data science. So, if you are a data scientist then you must master this great data visualization tool. It is a robust tool and can make your work very easy.