{"id":250411,"date":"2023-04-07T13:40:35","date_gmt":"2023-04-07T13:40:35","guid":{"rendered":"https:\/\/imarticus.org\/?p=250411"},"modified":"2024-01-23T11:19:08","modified_gmt":"2024-01-23T11:19:08","slug":"data-science-using-tableau-and-power-bi","status":"publish","type":"post","link":"https:\/\/imarticus.org\/blog\/data-science-using-tableau-and-power-bi\/","title":{"rendered":"Data Science Using Tableau and Power BI"},"content":{"rendered":"

Data science creates coherent knowledge from incoherent structures of data using statistical processes and tools. In a world where technology reigns supreme even for the most minor issues, data science is a rapidly developing sector and is quite beneficial for anyone interested in exploring this area.\u00a0<\/span><\/p>\n

To understand and work with data science, one has to be familiar with the workings and significance of the tools used to arrange unstructured data. These include <\/span>Tableau <\/span>and <\/span>Power BI<\/span>, two of the most widely used analytical tools in organising data.\u00a0<\/span><\/p>\n

Read on to learn how a knowledge of these tools can help make a successful career in data science<\/a><\/strong>.<\/span><\/p>\n

Data visualisation and its endless merits<\/strong><\/h2>\n

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Before using tools like <\/span>Tableau <\/span>and <\/span>Power BI<\/span>, it is imperative to know what data visualisation is<\/a> and how it works. Imagine reading about the population statistics of a country over decades- the changes in the numbers become a lot easier to understand when presented with graphs or pie charts.<\/span><\/p>\n

These graphs and charts in data visualisation are often created with the help of the programming language Python. <\/span>Data visualisation with Python<\/a><\/strong> allows it to use libraries like Bokeh and Matplotlib, which contain unique intrinsic units, to create the required graphs from a mass of unstructured collected data. <\/span>Tableau and Power BI<\/strong> help enhance such effortlessly receptive graphs and more. They also employ <\/span>linear regression<\/span> when sorting data- it helps predict the outcome of the dependent variables on the independent ones during data analysis and assists in data visualisation.<\/span><\/p>\n

Data science using Tableau – Its uses and importance<\/strong><\/h2>\n

Any organisation needs its data to be analysed in order to understand its progress and targets and take corresponding action. Founded in 2003, <\/span>Tableau <\/span>enters this scenario as an essential analytical tool that helps process the sea of data into great visuals allowing Data Scientists to understand and extract relevant information from the same.<\/span><\/p>\n

How Tableau operates<\/strong><\/h3>\n