Mr. Gaurav is a cybersecurity engineer, developer, researcher, and Book-Author who did his B.S.-Cybersecurity from EC-Council University & Masters from LPU. He is an India Book of Record holder, Guest speaker with 7+ years of experience in IT.
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Data is the new oil for every industry. Every year, organizations collect massive volumes of data of all sizes. Such data help in making informed decisions and findings. Every organization is data-driven and relies on data to edge out competitors, and make profitable decisions. According to some predictions, by 2025, users will generate nearly 463 exabytes of data each day. But many organizations do not use the proper tools and applications to extract meaningful insight from the harbored structured and unstructured data. In this article, you will learn about Tableau features and how businesses utilize this visualization tool for data science. KnowledgeHut offers Tableau for Data Science course for learners looking to leverage the data science capabilities of Tableau.
Tableau is an incredible data visualization and business intelligence software that helps in generating graphics-rich reporting & analyzing enormous volumes of data. This American company started in 2003 and got acquired by Salesforce in June 2019. Enterprises use Tableau for mining actionable insights from granular data. It offers a plethora of features and customization within it. Almost all fortune 500 companies are leveraging Tableau for extracting better data-driven insights & understanding as per the market demands. More than 63,298 companies are using Tableau, and the count makes the market spread of 6.26 percent.
Through Tableau, data science professionals can generate graphs, charts, maps, data-driven stories, dashboards, etc., for visualizing and analyzing data. Rich visuals and data interpretations help business executives make efficient business decisions. There are four different products Tableau caters to for the organization. These are:
Working on data science with Tableau becomes beneficial because Tableau caters to a wide range of data visualization tools, features, and techniques that help in comprehending data easily. KnowledgeHut’s applied data science with Python can give you a clear understanding and hands-on experience on data science tools like Tableau.
There are various data visualization tools and libraries available in the market. But most organizations prefer Tableau for data science work because of its varied features. You can enroll in Data Visualization with Tableau Training and dive deeper into visualization techniques and how Tableau makes a difference.
Some of them are:
All of these justify the fact that Tableau is an enabler for data science. Since Tableau is good at empowering meaningful data-driven acuity through rich visuals, data analysts & professionals find it a great tool to showcase their analysis through graphs, charts, and other graphical representations.
Tableau plays a significant role in data science; the benefits of Tableau don’t stop at that. It also helps improvise various forms of data-driven insights generated by data scientists. With tools like Tableau, data science professionals and data scientists can extract & evaluate complex data. Tableau helps in generating a relationship among distinct variables for making predictions from messy datasets. Therefore, to become a data scientist from a data science professional, proficient knowledge of Tableau is a must. So, data science aspirants and professionals must leverage the benefit of the best online data science courses with Tableau provided by KnowledgeHut. Here are some of the pivotal points that benefit data scientists in their day-to-day work.
There is a significant contribution of Tableau for data science. There are a lot of uses Tableau caters to in data science, and organizations are leveraging it to present the data in graphical format. That helps the top-level executives and business shareholders make informed decisions. If you are looking for no-code or low-code data-driven visualization solutions for your company, Tableau is the best and easy-learning tool. You can also check out the best online data science courses with R, Tableau, and Python provided by KnowledgeHut.
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Answer: It takes roughly around 2 to 6 months to learn Tableau. It is simple to understand but usually needs a longer time to master all the different functionalities. If you have experience with data visualization and data science concept plus, you give hours of dedicated learning, then 2 to 3 months makes it enough for an aspirant to master it.
No, it is not mandatory or a prerequisite to take up any programming language (like Python) for learning Tableau.
Answer: It is not necessary to learn Tableau for data science. One can use visualization libraries or other tools like Qlik for doing the same work possible using Tableau. But since Tableau is a clear market leader in data visualization, it has become a must-have application for data analysts.
Yes, data analysts use Tableau. Once they refine the granular data required for making informed business decisions - these data are feed to Tableau for providing rich visuals. As we all know, better visuals help acquire a clear prospect towards decisions. Proper use of Tableau is essential to learn for data analysts. You can look for the Tableau Data science course from here.