How much time will it take to learn data analysis with Tableau?

Big Data Analytics Course

Data Science and Analysis are among the most highly-demanded branches of computational advancement. It wouldn’t be wrong to say that these fields are driving most of the progress we have seen in recent times. 

If data has been referred to as the new oil, then data science and analysis are the oil rigs pumping oil 24x7x365 and driving the world towards a better tomorrow. However, if you want to learn data science or analysis today, you must also know Tableau. 

But is Tableau easy? How much time will it take to learn data analysis with Tableau? Let’s find out.

What is Tableau, and what is its significance in Data Science and Analysis?


Tableau is one of the inevitable courses in Data science and analysis. Many data science and analysis aspirants wish to learn Tableau but often have some misconceptions. They think learning Tableau requires technical training of some sort. So the learning curve might be steep. 

But there is no truth to this. Tableau is not technical at all. Its difficulty level might be equal to that of Excel. You need two to six months at the most to master it.

Basic Tableau is not difficult at all. First of all, let us bust one myth. You don’t require any background in computer programming to master it. Although data analysis might require you to learn a bit of Python, that’s all it is. Tableau does not require you to learn any programming language whatsoever. 

It helps you to represent the data pictorially. Grasping Tableau requires you to understand how its interface works. Once you figure that out, you are good to go. If you have some basic understanding or have used it beforehand, you might also get a head start and complete the course easily. Only three months are required at maximum to master it.

However, if you are starting from scratch, you might need to understand the basics and all the stuff that you see on Tableau’s UI. Then you might need six months to learn every bit of the data visualisation tool.

As already mentioned above, Tableau helps us to visualise data. You need to feed in data as a CSV sheet, and you will be able to get a visual output out of it. This way, you can understand what all perspectives can be generated from the data. 

Using these data visualisations, you can make precise solutions driven by the data. There are also some elements of business intelligence along with analytical tools. Tableau has mind-blowing software which can convert raw data into a dashboard that you can access. 

Data gets simpler after depicting it visually, and it is then human professionals interpret. They better understand the KPIs (key performance indicators) and provide a better solution to a problem. Those opting for a PG in Data Analytics must choose a course that teaches them Tableau.

The other advantages are that Tableau performs the data analysis extremely quickly, almost in real-time. Visualising data is also stunning, making you understand all the data projections and statistics very easily. It eases the understanding process for data analysts and other professionals. Since Tableau doesn’t require any technical background, the data visualisation can be understood by every person in the company, regardless of their professional background.

Other great features of Tableau provide a great advantage to Data analysts as they get more power in their hands. You get options like data blending, which allows you to display data from other sources and perform a comparative analysis. With the help of the data blending feature, you can even find out how well you perform against your competitors.

Then there is a collaborative feature of Tableau. You can use a collaboration kit to use the data for reference and comment on it. Since Tableau does not allow and save work in one workbook, you might have to use several collaborators to make the data interactive and more useful for comprehension.

Tableau also allows users to manipulate live data sets. This way, a data analyst can save a lot of time on data wrangling and extract a lot of information from the given dataset. The output generated from the raw data is more accessible and comprehensible. So Tableau is a useful tool for data scientists and analysts.

So if you plan to become a data analyst, you need to learn and master Tableau. You also need to check whether this is a Data analytics course with placement. Doing a job is the best way to master a skill. But it is going to take some time. That is why you need to enrol in the PG Data Analytics course offered by Imarticus, where all the things mentioned above will be taken care of. So, don’t wait; enrol now. 

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