Tableau for Beginners – Data Visualisation made easy

Pavleenk Kaur 23 Feb, 2024 â€¢ 18 min read

Introduction

The idea is to go from numbers to information to understanding â€“ Hans Rosling

Have a look at the visualization below, which was created by a famous Swedish statistician, Hans Rosling. He compiled roughly 200 years of World Development Data and presented it in a very simple manner:

This above is an excellent example of Data Visualisation, which rather than focusing on what the numbers are, focuses on telling their story. You can find the interactive version of this visual here.

There are multiple Softwares that are available now at instant access which assists in such easy visualizations and one tool that we are going to cover in this article is Tableau.

Note- If you want to learn beginner-level Tableau in a course format, have a look at our free course- Tableau for Beginners.

Sample Dashboard in Tableau

What can you make out from the picture below?

This Dashboard, made on Tableau, visualizes a Supermarket’s Sales and Profit Analysis.

At a glance, you can see:

1. The Sales distribution of various categories relative to each other
2. Their respective Profit margins.
3. Each Categoryâ€™s Sub â€“ Category Product Sales
4. And finally, the Sales growth of Categories over the years

So, in this article, we will learn how to make such simple visualizations in Tableau to understand our data well.

Overview of Tableau

What is Tableau?

Tableau is a Data visualization tool widely used for Business Intelligence but not limited to it. It helps create interactive graphs and charts in dashboards and worksheets to gain business insights. And all of this is made possible with gestures as simple as drag and drop!

What Products does Tableau offer?

What do you need to know before using Tableau?

You donâ€™t need to know much to use Tableau, but a basic awareness of all the types of graphs, such as bar graphs, line charts, histograms, etc., is still preferred.

It will also be beneficial if you possess some basic understanding of database management ( datatypes, joins, drill down, drill up, etc ). Even if you donâ€™t, it is not a reason to worry since I will be covering all such concepts in this and forthcoming articles.

Installation

To work on Tableau, you need Tableau, right?

Tableau Desktop, Public, and Online offer Data Visual Creation from the five above-mentioned products.

Tableau Desktop

It is available in the following three formats :

1. Free trial for 14 days
2. If you are a student or a teacher, you get free access to the Desktop for a full year.
3. Purchase Tableau

Tableau Public

Tableau Public is purely free of all costs and does not require any license. However it comes with a limitation: All of your data and workbooks are made public to all Tableau users.

Tableau Online

Tableau Online is the best option for you if you wish to make your Workbooks on the Cloud and be able to access them from anywhere.

Getting Started

Now that you have the suitable product installed and set up, I am pretty sure your hands must be tingling with anticipation to begin visualizing using Tableau finally! Well, letâ€™s not keep you waiting. Go ahead and launch the tool.

Connect to the Data

You should see a screen similar to the one above. This is where you import your data. As is visible, there are multiple formats that your data can be in. It can be in a flat file such as Excel or CSV, or you can directly load it from data servers, too.

You can see that Tableau itself offers some Sample Workbooks with pre-drawn charts, graphs, and other visuals. I would suggest going through these later for further exploration.

The best way to learn is to get your hands dirty. Let us start with our Data, which can be found here. The data is that of a United Statesâ€™ Superstore deliberating over its expansion. It wishes to know the prospective regions of the country where it could and hence requires your help.

The first thing that you will need to do is import the data onto Tableau. So quickly follow the below steps:

1. Since the data is in an Excel File, click on Excel and choose the Sample â€“ Superstore.xls file to get:
1. You can see three sheets on the screen, but we are only going to be dealing with Orders here, so go ahead and drag the same on Drag sheets here:

Uh oh, the imported data looks a bit different for the first few rows. Donâ€™t worry; the solution lies right ahead.

Data Interpreter

3. Do you see the option to use Data Interpreter?  Click on it to get the following clean view:

All that messy data magically disappeared!

If you open the Excel data file, you will see some metadata in it, i.e., information about data :

Tableau imports the entire data file as is, but, anticipating such discrepancies explicitly provides a solution as a Data Interpreter. If you wish to view the exact changes that it made, click on Review the results and choose the Orders tab in the opened Excel sheet.

As it will show, it simply removed the erroneous data.

Data Visualisations

As soon as you have imported your dataset, next to the Data Source tab near the bottom of the screen, you immediately must see Go to Worksheet. A Worksheet is where you make all of your graphs, so click on that tab to reach the following screen:

Donâ€™t get overwhelmed by the various elements that you see here, we will cover them all one by one.

Letâ€™s start with Dimensions and Measures:

Moving onto Shelves :

Visualization in Tableau is possible through dragging and dropping Measures and Dimensions onto these different Shelves.

Rows and Columns : Represent the x and y-axis of your graphs/charts.
Filter: Filters help you view a strained version of your data. For example, instead of seeing the combined Sales of all the Categories, you can look at a specific one, such as just Furniture.
Pages: Pages work on the same principle as Filters, with the difference that you can actually see the changes as you shift between the Paged values. Remember that Rosling chart? You can easily make one of your own using Pages.
Marks: The Marks property is used to control the mark types of your data. You may choose to represent your data using different shapes, sizes or text.

And finally, there is Show Me, the brain of Tableau!

When you drag and drop fields onto the visualization area, Tableau makes default graphs for you, as we shall see soon, but you can change these by referring to the Show Me option.

Note: Not every graph can be made with any combination of Dimensions or Measures. Each graph has its own conditions for the number and types of fields that can be used, which we shall discuss next.

Various Graphs and Charts

So far, we have pretty much covered the requisite theoretical knowledge. Lets finally begin with some visualizations now.

I personally prefer to start from the shallow side of the pool, slowly swimming towards the deeper end. So I would suggest beginning by getting an overview of the Superstore Sales and Profit Statistics. That would include the Net Sales, the Net Profit, and the growth of the two measures, to name a few. Here is a gist of what we will be making :

From what can be observed, the net sales are on the rise, but the Profit is creeping up slowly. We can also quite clearly see the peak Sales Months, which could be attributed to various reasons. We can only know more as we explore more.

Before we start, there is one thing that I would like to recommend and that is you name your Worksheets as being done here. Since I will be referencing them back and forth throughout the article, it will be easier for you to follow.

Letâ€™s begin with the simplest visualization, which is displaying the Net Statistics numbers. Tableau, being as smart as it is, automatically computes such values under Measure Names and Measure Values. Follow these steps to make what is called a Text Table :

1. Drag Measure Names from Dimensions onto the central empty area to see a Text Table.
2. Measure Names will be displayed automatically onto Rows, so drag them from Rows to Columns.
3. Since we donâ€™t really need Measures like the Row ID, Discount, etc, you can drag them off from below the Marks Pane to get something like this :

Note: Donâ€™t get confused by the different colors of the fields that you see. Just remember one small trick: Blue means Discrete and Green means continuous.

So we have the net Sales and Profit values, letâ€™s delve a little deeper by getting the Sales and Profit Values over the years. Letâ€™s make another, but a more detailed, Text Table :

1. Drag Order Date from Dimensions and Sales from Measures to Rows.
2. Right-click on the green Sales Pill, and select Discrete instead of Continuous since we want the explicit values and not the bar graphs.
3. Finally, drag Profit on the â€˜abcâ€™ column to get :
4. Do the same thing for Monthly Sales and Profit Values, but this time change the format of Order Date from Year to Month by right-clicking on Order Date in the Rows and choosing Month to get something like this :

We have just covered the numeric part of the Dashboard, but that is not its selling point. Itâ€™s the Line Charts. Let’s quickly learn how to make one :

1. To create the chart of Sales and Profit Growth, drag Order Date over the Columns, Sales over Rows, and then Profit over the formed Sales axis â€“ so that you see an equals sign â€“ to get the following :
2. Repeat the same to find the Peak Sales and Profit Months, but again change the format of Order Date from Year to Month, and get:

If you were to click on Show Me, you will see the different types of Line Charts that you can make, and if you were to hover over each of them, you will get to see their Dimension and Measure requirements too. In case you ever feel lost, I recommend referring to Show Me.

With the previous visualizations, we had gotten a brief overview of the Superstore. Letâ€™s dig a little deeper now. The next thing that I can think of exploring is the demographic of the Sales and Profit. What are the States that have the highest Sales Revenue, which ones are generating the maximum Profits:

Before discussing the inferences, letâ€™s first create the Pie Chart of Region Sales :

1. Drag Regions onto Rows and Sales onto Columns.
2. Go to Show Me, and select the Pie Chart.
3. And finally, drag Sales over the Label in the Marks Pane to get :

From the visual, itâ€™s pretty evident that the two opposite ends, East and West are leading in the Sales game. Letâ€™s dissect this a bit more.

Note : Whenever you have some geographical data, it is always advisable to plot and see it on a Map to gain better insights.

So, we are now going to make the Map Chart of State Sales Distribution :

1. Since it is the States that we wish to analyze, drag States onto the empty area so that you automatically see a Map with small Circles. Follow this step by dragging Profits next. You will notice the size of these circles changing to represent the varying values of Profits. This is called a Symbol Map. But we will convert this into a Filled one by going to Show Me and selecting the Filled Map.
2. Drag Profits again, but this time onto Label in the Marks Pane, to view the Profit Values mapped as well, like so :

California and New York are the top most sellers from the West and East region, but unfortunately, there are other states such as Texas, Colorado which even after having good Sales, have negative Profits! This is certainly not good news for the Superstore. You can perceive a good analysis for the other States as well.

And lastly, here are the steps for making the Scatter Plot of Sales and Profit Analysis :

1. Drag Sales onto Rows and Profit onto Columns. You will see one tiny circle representing the Total Sales and Profit Values.
2. To get more information, drag States onto the graph created so that these circles/bubbles scatter to represent the individual States.
3. To better understand the central tendency of the data, we have also added a Median axis as a Reference Line. This can be done by right-clicking on the Sales / Profit Axis – > Adding Reference Line and choosing Median over the default Average Reference.
4. Finally, for some more insight, drag States again, but this time onto Label in the Marks Pane, and get:

The findings from the Map chart become more prominent with the following Scatter plot inferences :

• The states in the top right, with high Sales and high Profits, mean good business for the organization.
• States with positive Sales and Profits, but near the two respective axis are the ones where there is some scope of improvement.
• Whereas the states that belong to the 2nd or 3rd quarter are the ones which are not generating much revenue.

One of the great things about Tableau is that it lets you interact with the visuals. Have a look at an example :

When we clicked on the Central Region, it highlighted and showed the Central States of the US, along with their respective Sales and Profit scatter. Here we used the chart as a Filter itself which is a feature of a Dashboard. We shall learn how to make one at a later stage.

There is one pretty important analysis that we have yet to touch, and that is Product Statistics. High Sales could be easily attributed to the high cost of the products being sold. Also, when you are considering expansion, you will want to know the Sales distribution of the Products too:

Here we have visualized not just the Sales but also the Profits.

It’s quite surprising to see Categories that have high Sales, generating negative profits, like Technology in November 2015, or Furniture in October 2016 and this is inferred from the first chart, which is also called a Highlight Table. As the name suggests, it highlights the relative proportion of the Measure Values of our data. So letâ€™s learn how to make one :

1. Drag Category and Order Date ( Year ) in Rows.
2. Drag Order Date (Month ) over Columns and Sales over the empty â€˜abcâ€™ fields
3. Select Highlight Table from Show Me, and drag Order Date ( Year ) back to Rows if it got re-shuffled.
4. Finally, drag Profits over Colour in the Marks Pane to get :

The Product Sub Category Sales is a Bar Chart, which is also quite easy to make :

1. Just drag Sub-Category over to the Rows
2. Drag Profit onto the Columns.
3. Go to Show Me and choose the Horizontal Bars
4. For some customization, drag Sales over Colour in the Marks Pane to attain this final visualization:

From the above graph, we get a good idea of the Net Sales and Profit margins of the various products. Notice that even though Tablesâ€™ Sales are quite high on the scale, itâ€™s the only product with the least profit.

Now, just like before, consider interaction with the visualization:

We can now view each Categoryâ€™s Productsâ€™ Sales and Profits at a low-level granularity of Year and Month!

Other Functionalities

Congratulations! You have now covered one of the important aspects of Tableau! But itâ€™s not the end of your learning just yet. Tableau offers some advanced functionalities, too, some of which we will cover next :

Filters

Until now, we have only made simple charts that provide cumulative data, combined data over the lifetime of the Superstore. To look at sales of a particular year or month for a certain product or to view the distinct aspects of the data, filters are the way to go.

Letâ€™s head back to the first-ever Chart that we made of Peak Sales and Profit Months :

The visual here is an accumulation of all 4 years of data, for all Regions, States, Categories and Sub Categories.

The steps of turning any Dimension into a Filter are the same. Letâ€™s first experiment with the Order Date ( formatted to Year ):

1. Drag the Dimension to the Filtersâ€™ Shelf to see the following pop-up. Here, we will be choosing Years :
2. Choose the values that you want to be a part of your Filter :
3.  Right-click on the newly generated Filter, and then choose Show Filter :
4. You can also change the format of your Filter, for example, whether you wish for a Dropdown list, a Slider, a Single Value List, etc :
5. If you feel that some of your filters can be applied to other sheets as well, then rather than repeating the steps, you can Apply the Filter to all other relevant Worksheets :

Drill Down and Drill Up

By now, you must have gotten some picture of how our Data is built. We have Category as the main Field, divided into Subâ€“Category, further distinguished into the various Product IDs and their corresponding Product Names.

This concept of breaking down our data to reach the absolute depth is called Drilling Down:

Similarly, you can drill down from Order Date to Order ID to Ship Date to Ship Mode. This is also referred to as making a Hierarchy of data.

Letâ€™s consider the ProductDrillDown first, which is a Bar Graph :

1. First, you need to group the Dimensions you want in a single Hierarchy. So, drag Sub-Category from Dimensions on top of Category in the Dimensions itself, and change the Name of the hierarchy to Product.
2. Now drag Product ID and Product Name over this Product Hierarchy
3. Do the same for Order Hierarchy to get :

4. To finally plot your data, drag the Product Hierarchy onto Rows and Sales onto Columns, and get:

This was just a simple Bar Graph, but you will see a small plus sign if you hover over the Category axis. Click on it to get a granulated version of your data. Do the same for the other generated axis as well to get to the absolute depth.

The Tree Analysis of Product Sales is a TreeMap, which is a great way of representing Drilled Down data and is quite easy to make :

5. Following the drill down from Step 4, simply go to Show Me and select the TreeMap chart, to get the following :

So far you have analyzed the present scenario, but for expansion consideration, letâ€™s try and analyze the future too.

With the following Dashboard, you can see not only the Trends over the Sales Months but also a Forecast over the Years. And both of them tell a different story altogether :

Although the Sales of the Superstore are increasing over the months of the year, the future, in general, looks a bit bleak. The sales seem to be constant for the next 3 years, but fortunately for the Superstore, the Profit is increasing steadily. Letâ€™s get to making the above now.

Trend Line

Traverse back to the Peak Sales and Profit Month Chart and follow these steps to make a Trend Line of your own :

1. Go to Show Me and choose the Dual Combination chart, to get this chart :

2. To get the Trend Line, go to Analytics, and simply drag Trend Line over the chart, to get :

Forecasting

For forecasting, we are going to deal with the Sales and Profit Growth chart. The construction is similar to that of Trend Lines, but with a small change. The steps are :

1. Drag Forecast over the chart.
2. You can also change the time frame of the Forecast by right-clicking on the Forecast Area and opting for Forecast Options, after which you can make your customizations:

Clusters

Letâ€™s head back to the Sales and Profit Analysis chart we made. Remember the detailed inference that we had generated from it? We will make that a bit more prominent now, using Clusters. To make them:

1. Go to Analytics and choose Clusters.
2. You can format the Cluster formation as per your wishes. Here, we are clustering based on the Sum of Sales and Profit, choosing the number of clusters to be 4:
1. To view the Cluster information, right-click on Clusters in the Marks Pane, and select Describe Clusters, to get this pop-up:

Dashboard

I am sure by now you must have gotten a pretty good idea of what a Dashboard is, having seen it plenty of times all throughout this article.

If not, well then a Dashboard is simply a means of combining Worksheets together so that they convey some message. Without much further ado, letâ€™s get right to it!

Consider the State Sales Distribution Map chart and Product Sub Categories.

What if you wanted to know the various Sales margins of each Product within separate States? We had observed that Texas was one of the States with the lowest Profits. By looking at the following Dashboard, you will see that the reason is itâ€™s not managing to generate Profits in the majority of the Products:

Now consider the state-wise Sales distribution of a Sub â€“ Category:

The above beautifully shows the distribution of Appliances nationwide, where California seems to be the major Profit contributor.

Making such a Dashboard is quite easy. Letâ€™s see how :

1. This time, instead of creating a New Worksheet, we will create a new Dashboard. Click on the window-like icon next to the â€˜New Worksheetâ€™ icon in the bottom panel to get the following:
2. See the multiple Worksheets we have made until now over on the left? All we have to do to make a Dashboard is drag these sheets from the pane to the empty area â€˜Drop sheets hereâ€™.
3. So to make the previously displayed Dashboard, drag State Sales Distribution and Product Sub Category Sales. The Dashboard will automatically make space available for both of them.

Note: Even after creating the Dashboards, you can still edit your Worksheets; the same changes shall be reflected here.

If you were to click on the States or the Products after creating your first ever Dashboard, you wouldnâ€™t observe any change. For such visuals, we first have to convert the Charts themselves into filters.

4. click on the small Down Arrow on each chart you wish to turn into a Filter, and select Use as Filter:

Note: While making Dashboards, it is preferred to use your charts as Filters, rather than cluttering up the view with custom ones.

Story – Bringing it all together

Just like Dashboards were a way to combine the Worksheets, a Story is where you combine all the dashboards and, if need be, individual Sheets as well to convey, as the name suggests â€“ a Story.

1. Just like before, you simply drag your Worksheets and Dashboards onto the empty space :

So, letâ€™s combine all the Dashboards we had made into what could perhaps make a decent presentation for a beginner. Do sure to Add a Caption to all of your Dashboards to convey your message clearly :

If you have ever come across Tableau Stories online, the ones which you could actually interact with, instead of just viewing, that is made possible by publishing your Workbooks onto the Tableau Server.

If you have one set up, then all you need to do, after creating your Stories, is go to Server -> Publish Workbook and enter the Server Name :

Conclusion

What we have covered so far is pretty much the basics of Tableau. It has various other features, which I will cover in my forthcoming articles.

As it is said â€˜With practice, comes perfectionâ€™, it is suggested that you experiment as much as you can with Tableau.

Below is a sample Dashboard that I would encourage you to try and make. You will get to test the skills you have learned so far and hopefully acquire more. The dataset used is the same as the one we have been working with so far :

This article explores key data science and analytics aspects, focusing on practical tutorials for effective data visualization. The author highlights the significance of clear visualization techniques using tools like Tableau, emphasizing calculated fields and creating impactful dashboards. With a blend of Microsoft Power BI and Python, the tutorial covers visual analytics, catering to data scientists and analysts. The narrative delves into machine learning concepts, considering real-time data points and efficient data storytelling. The article hints at future explorations of advanced features while offering insights into Salesforce integration and SQL proficiency for comprehensive data analysis.

You can also check these articles – Guide to Learn Advanced Tableau

We have also created a free course for you to understand the topic in a structured manner- Tableau for Beginners

Frequently Asked Questions

Q1. What is Tableau Data Visualization?

Ans. Tableau is a leading data visualization tool that translates raw data into interactive and understandable visualizations, such as charts and graphs, aiding in data analysis and interpretation.

Q2. Can I use Tableau for free?

Ans. Yes, Tableau offers a free version known as Tableau Public. However, more advanced features in Tableau Desktop and Tableau Server require a paid license and you can check pricing on tableau website.

Q3. Why is Tableau the best Visualization tool?

Ans. Tableau is considered the best visualization tool due to its user-friendly interface, extensive visualization options, real-time data connectivity, and seamless integration with diverse data sources.

Q4. Can I use Tableau for Data Analytics?

Ans. Tableau is used in data analysis to visualize complex datasets, facilitating tasks like business intelligence, performance analysis, market research, and informed decision-making.

Q5. Can I do Data Visualization With Tableau?

Ans. Data Visualization with Tableau involves leveraging the software to transform data into meaningful visual representations, including dashboards, charts, and graphs, enabling effective communication and interpretation of insights.

Pavleenk Kaur 23 Feb 2024

Pavleen is a Masters' student at University of Southern California, pursuing Data Informatics. She aims to acquire knowledge and expertise in Data Science, so that she can discover opportunities of using this field for social good.

Responses From Readers

Gopika Bhardwaj 27 Jul, 2017

A very informative article

Deep Chatterjee 27 Jul, 2017

Awesome article! Very interestingly and informatively presented. Thank you.

Vikram 27 Jul, 2017

So comprehensive! Thanks! I have a question, do let me know if you have any insights on this. Is tableau planning to have a software package for Linux? I can see that it supports only windows and Mac!

Ghazi Salahuddin 27 Jul, 2017

A very useful article.. It will surely help us..

rams 27 Jul, 2017

Hi Pavleen, The very first step isn't working for me :( , once I dragged I dint get any Text Table 1. Simply drag Measure Names from Dimensions onto Columns. Please help

vinit777 27 Jul, 2017

Very Nice explanation Pavleen

rams 28 Jul, 2017

The screen shots and the steps illustrated do not match at few places and is bit confusing, could you please take care of them to avoid confusion.

Shirish 28 Jul, 2017

Thank you for sharing this knowledge very helpful....

Asutosh 28 Jul, 2017

Hi Pavleen, Very nice and informative article. I am facing problem when trying Map Chart of State Sales Distribution: When i dragged the STATES onto the blank area, i got a map, but on subsequent steps where i should be getting Symbols according to Profit values, i am not seeing any circles; also when i convert it into filled map chart, respective states are not getting coloured as desired.

Jinson Fernandez 29 Jul, 2017

Nice and informative article..... Can you suggest some good blogs specifically on Data Cleaning and pre-processing with Tableau.

TecCrowd 29 Jul, 2017

Thank you so much for sharing this helpful knowledge. I have learned a lot.

Shashank Saksena 29 Jul, 2017

Superb and Awesome Article for the ones who really want to dive deep!

Hunaidkhan 01 Aug, 2017

Very detailed article Pavleen, this will surely help all the tableau beginners learn data visualization. Hope to get some more articles on Tableau in the future.

Jay 02 Aug, 2017

Great Article. Would you be able to republish on https://imadata.ninja/blog/

Abhinav Jain 03 Aug, 2017

Superb article. Explained each step very well and easy to follow. Looking forward to seeing more on advance functionalities of Tableau.

Roberto 03 Aug, 2017

Thank you Pavleen. In this side of hearth iÂ´m using Lumira, you have any ideas for this platform?

Raj S 06 Aug, 2017

Good work putting all core purpose of Tableau on one page.. Way to go!

Kaushik 07 Aug, 2017

Extremely helpful for a starter..a very enjoyable learning. Thanks Pavleen for your hardwork to share this with us. Eagerly waiting for your next one.

Ramdas 09 Aug, 2017

Excellent article Pavleen, nice description of different features available within tableau...A very good base to get started in tableau.

emma 22 Aug, 2017

Thanks for the information. The information you provided is very helpful for tableau Learners .

Manu 25 Aug, 2017

Very well explained and easy to follow article. Thanks for the efforts. Keep up the good work of sharing these wonderful articles.

Carlos 30 Aug, 2017

Very clear and helpful.

Deepak 06 Sep, 2017

this website is awesome, Thanks a lot for making data science so easy. Great work! Keep it up !!

Niks 11 Sep, 2017

Hi Pavleen Awesome article.When are you planning to post the advance one. Waiting Eagerly.

Leviya Bl 23 Sep, 2017

Thanks so much for writing this article. This is probably the best one by far. Easy to understand and educate myself on scala and how the best way to go about it. Thanks a lot really appreciate you sharing with us. The information you provided is very helpful for Tableau learners Learn aboutTableau Server.

Leviya Bl 23 Sep, 2017

Thanks so much for writing this article. This is probably the best one by far. Easy to understand and educate myself on Tableau and how the best way to go about it. Thanks a lot really appreciate you sharing with us. The information you provided is very helpful for Tableau learners Learn aboutTableau Server.

Nikhil 03 Oct, 2017

Hi pavleen can We expect your next advance article on tableau this month? i have to prepare for the interview.

Henok 20 Feb, 2018

Awesome article!!!

Arka 25 Mar, 2018

hey! the dataset doesn't exist in Github repository. Please look into the matter.

Atulkumar Bhoyar 05 Apr, 2018

Good and Knowledgable article hats to you

Saral Gupta 15 Apr, 2018

Hey, nicely explained! I have a quick question on parameters: How are they different from filters?

Jeremy 12 May, 2018

Great work. Thanks!

Palas 20 Mar, 2022

Using this Tableau tool data analysis and data visualization is very easy and accurate. Nice information on this tool. Thank you

SANJEETA 08 Jun, 2022

Awesome, I have learnt many things about tableau. Thank you so much for this informative notes. This is really helpful for beginners.

sandeep 10 Aug, 2022

Informative blog, thanks for sharing.

joaquin 18 Aug, 2022

Excellent and informative post. Continue to post.

joaquin 18 Aug, 2022

Excellent and informative post.Tank you .

Darshan 28 May, 2023

Great work!!!

CRG Solutions 09 Jun, 2023

Hi, You explained everything very nicely. Thanks for all the information.

Jonan 11 Jun, 2023

Absolute Legend ! I have an interview tomorrow for a data visualisation developer and we got a task to visualise data. And this is Golden ! Thank you so much