Tag Archives: data visualization courses in pune

5 Ways to Enhance Value of Your Dashboards Using Maps

Today, an effective dashboard is mostly insight-driven. And since a good lot of analysis projects stand upon spatial data, playing with maps is an indispensable skill you need to have in your visualization toolbox.  

5 Ways to Enhance Value of Your Dashboards Using Maps

Here, we will like to share a few handy tips to improve the analytic and aesthetic value of maps in your dashboard:


Making Data Visualizations Smarter, Tableau Explains How

Making Data Visualizations Smarter, Tableau explains How

Appalling, bewildering and utterly nonsensical – data at times can look incomprehensible, especially in its raw forms. This accelerated the foundation of the data visualization company and our very own ‘business dashboard’ tool. Generally found locked within the so-called BI sphere, we can now consider these top notch graphical tools as a powerful medium of assimilating, categorizing, analyzing and then presenting data in a highly interactive and interesting form, using images and charts.


What Makes Tableau 10 So Desirable Among the IT Nerds

Your data just got better, say thanks to Tableau 10. The big data geeks have worked on both the beauty and brains of Tableau, to make the analyses easier, faster and exceptionally delightful. Tableau 10 features an exciting new look and feel, loaded with cute fonts and beautiful colours to make your viz sparkle.

What Makes Tableau 10 So Desirable Among the IT Nerds

We are thrilled. We have been waiting for days to gauge how some of the Tableau 10 new features will synchronise with our conventional business interface for Hadoop. We have culled out some of the best features of Tableau 10, which had made us zealous and left us buzzing. And here they are ..


Demystifying Tableau Jargons: Interact With Data like Never Before

Demystifying Tableau Jargons: Interact With Data like Never Before

Businesses are flourishing. Managerial data are in abundance. The need for efficient BI softwares is at the pinnacle. Structured BI softwares are nimble and up to the minute. Tableau is one such BI tool, which is not only simple and comprehensible, but also extremely purposeful, enough to fulfil high-end professional commitments. It works just the way you want it to, instruct it in a particular way and wait for the results, without compromising the security of various confidential data.  


Power BI or Tableau? Which is Better and Why?

In the present data frenzy setting, data visualization is the new Talk of the Town. Various companies are developing and launching their own data visualization tools in the market. For quite some time now, Tableau has been the pioneering data visualization platform and till date the best to consider. Tableau’s data visualization tool is unbeatable to any other emerging product in the digital community. 




Apparently, Tableau has a remarkable competitor, recently. It is the Power BI, a decisive and dynamic BI tool, brought into by Microsoft. It is catching the trend with Tableau fast and appears to be on its way to become the number one BI tool in the digital market.


ETL and ETL Testing: The Concepts Explained

In this New Age, businesses pay maximum attention in collecting customer and transactional data. Businesses with draconian financial reporting and persistent audit requirements look up to ETL, as it offer an organized and integrated solution instead of relying on other apparent solutions like Hadoop.



ETL and ETL Testing: A Detailed Evaluation

 From Visually.

Battle the Blank Tableau Canvas Blues with These Nifty Tips

Battle the Blank Tableau Canvas Blues with These Nifty Tips

Do you experience vizzer’s block? Do you feel paralyzed by choices? Do you stare at the blank Tableau canvas, wondering from where to start your viz?




Though brimming with stories to tell, you are stuck at the get-go. Fortunately, here are a few tricks to help you get over the blank-canvas woes and get yourself rolling.

Draw your mind out

Doodling does help! Draw, doodle or sketch, just kick-start your cognitive thinking abilities. The scribbles don’t need to be pretty or legible, but they have to spur the creative process. So, grab a paper and pen, and start brainstorming.




And, you don’t have to go it alone. From academic researchers and lifestyle bloggers to professional visual consultants, the entire world is drawing.

Get inspired by ace visualizers

People inspire you, or they drain you – pick them wisely. Keep the right people by your side, they will lift you up and get the better out of you. Be in association with hotshot vizzes, follow maven data journalists and data vizzers, jot down notes and read data-viz pdfs.


 ALWAYS, keep your eyes open to stumble across fetching viz, whose idea might work out well for you!

For example, this visualization by Washington Post tells a gripping food-survey story.




Develop a formidable structure to understand the data better

Frazzled about starting your viz? If affirmative, then this checklist can save your day. It is segregated into two parts – data preparation and data exploration.

Taking the first one first, i.e. Data Preparation:


As boring as it sounds, physical inspection of your data sometimes helps you comprehend the data set’s possibilities and challenges. To draw a clearer picture, here are few things to look into a data set:


  • The kind of data in each field
  • The pattern of data structure and format
  • Fields covered and not covered by the data set
  • Highest and lowest values in each field
  • Are there fields that contain null values


If you follow the above example, you will find there are multiple levels of data infused in the food-survey data set – where some food items boasts of four sub-categories, while others has only two. Situations like this make it hard to establish a comparison between two food items unless you know that they are at their minimum sub-category.




Coming to the second one, Data Analysis:

Analyse a data set just like interviewing it. Whenever you feel like going blank by staring at a Tableau canvas, start grilling yourself about data. Do it in a traditional interview way and you are sorted.

  • What, how, who, why, when, and where – Evaluate each field and ponder how to apply these questions on each field.
  • Let your inner child smile, while you ask “Why? Why? Why?” to your data.


To pop colours on your blank-canvas, interviewing is indispensable.


Remember: Every end is a new beginning

What if my final viz fails to shed light upon the deepest cognizance? Or, how will I feel if my viz cannot do justice to my story. Don’t worry, pondering is common. Get up and hit the road. There are countless number of ways to address a viz and remember that once you finish a viz, it doesn’t mean an end. Remaking and telling stories in newer and innovative ways are something you can always look up to anytime.



Turn the volume up and focus

Crank up the music, boost productivity and tune out distractions! Music helps in focusing on work, by diminishing outside noise (phone buzzing, colleagues chatting, TV blasting). Irrespective of the kind of tunes you like, plug in your headphones and say goodbye to the world!




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5 Tips for Creating Different Map Styles in Tableau

Let us not waste any time on reading long-worded introductions, and get right down to our 5 top tips for creating different map styles in Tableau.

5 Tips for Creating Different Map Styles in Tableau

You will be able to find out about these tips and a lot more on Tableau with our Tableau training courses.


  1. Removing map layer:


A simple way to create a clean map for best visualization is by removing the map layers. In order to do this, all you need to do is Select Map on the toolbar menu and “map layer”. Then simply click on the uncheck box and everything in the map layer window, this will leave behind only the outline of the map data.


Sherlock Holmes Has Been Doing Data Visualization Before Big Data

Investigative minded people will definitely relate to this story from almost every child’s formative years. The day they get their hands on a magnifying glass, kids would feign being the most famous detective of all times – Sherlock Holmes with a cap they would focus the magnifying glass on an object and try and derive meaning by studying the details closely. This would be their first lesson in data visualization. Later as we learnt about Mr. Holmes through books of Sir Arthur Conan Doyle many of us may have imagined pursuing a career as a full-fledged detective. In his book A Study in Scarlet is the most vivid description of the inclination Mr. Holmes has for the sciences.

Sherlock Holmes Has Been Doing Data Visualization Before Big Data

Now that we come to think of it a detective has probably evolved in this technologically driven planet into a modern-day data analyst or an experimental scientist. The job of a data analyst or scientist revolves around gathering a bunch of disorganized data, and then we use this to build a case through deduction and logic and then you reach a conclusion after analysis.