Why does your Business need Data Visualization?

December 6, 2021

In the current times, every business collects a vast amount of data. From app usage statistics to repeat purchases stats, from time spent on the app to the location of buyers, almost every data point is collected and stored in databases. We all know the importance of data in the growth of the business. From stocking inventory in anticipation of demand to focusing on more profitable customers & areasand optimizing employee productivity, data gives us accuracy. But it is helpful in the growth of our business only if we can draw insights from it and make better decisions.

Data is helpful but raw data isn’t 

Data helps in better and informed decision-making. But in most cases raw data does not make any sense, does it? Here are some of the pictures of data stored in databases in CSV, text or JSON format.

CSV Data

Fig 1: Customer’s Sales Data in CSV 


Fig 2: Yelp Restaurant Data in JSON 


Fig 3: Sample Employees Joining Info in a Text file

This is just lines and lines of data without any insight. All this raw data cannot help in decision-making unless we do something with it.  

Here comes the magic of visualization.
Data Visualization

Fig 4: Highest sales Customers by their geographic location 

Once we have processed the data and visualized it, how easy is it to make sense of those numbers!! Like in the above picture, we can see which geographical areas had the highest sales and can then devise a strategy accordingly to suit our business goals. 

Journey from Raw data to a beautiful Visualization 

We collect more data than ever before. Visualization can help uncover insights from the data and enable us to quickly pinpoint the pain points as we can process visuals faster and better than text (thus the saying, ‘A picture paints a thousand words).  

So why not leverage our inherent strength for better decision-making? 

But how to go from raw data to visualization? These are the steps we should follow to get to a stellar visualization that will offer us beautiful insights. 

Frame a question to ask the data –

Raw data is just like raw food. First, we have to decide what we want to make. Similarly, we must decide on the questions we want to ask and then process data accordingly. Lets say, we have data from a chain of superstores in the US and we would like to forecast the sales for next year. 

Reduce/Add to make it relevant data –

Suppose we want to know what items to stock in inventory for the Diwali season. Then it is imperative to take the data from Diwali months from the database. Usually, the data is holistic and captures all the information. It may or may not be relevant to our task. Therefore, it is imperative to reduce it to the relevant variables. More relevant the data, the more accurate information we can extract in visualization.

  • It would require us to make connections between the ‘Orders’ table and the ‘Returns’ table.
  • Now we have the complete data to predict sales. 
Data Cleaning –

The next step is to clean the data. Usually, the data has a lot of missing values, inconsistent data format, etc. Before we can. By descriptive statistics, we can find the holes in our dataset and then clean it. Fill in the missing values through average or median, treat outliers, convert string to numbers, etc. Now the data is ready for visualization.

  • In Tableau Prep, you can visualize the changes that you want to make to the data. Like removing the missing values, fixing data types, making joins and connections between tables, etc. All you need to do is, add step and you can clean the data, aggregate, make pivot tables, etc. 
  • The final cleaned data will look like this –       


Visualize –

Now is the time to use those fancy graphs and charts. Depending on the need and data size, from simple charts in Excel and Google data studio to modeling and visualizing complex data in Tableau, we can visualize the way we want as per the requirement.

      • Like we wanted to forecast the next year’s sales. Start by opening up a worksheet and name it Sales Forecast. 
      • Now since we want the forecast for the next couple of months, let us categorize order dates by month and put it into the column section and Sum of sales in rows.
      • To have granularity, let us divide it Segment wise by adding Segment in the row section. 
      • Using Filters and Marks for better clarity and visualization Since we have already divided our forecast segment-wise. We can use colors in the marks section for different colors for different segments. Just drag and drop segment to Marks and change it to colors. If you want, you can further use filters say by Order date or Region. 
      • The final visualization will look like this 


Don’t forget clarity – 

This is where experience in visualization will play a major role. It is extremely important to choose the right graph to visualize. Say, if we want to show market share, pie charts will be a better choice, scatter plots in case of the relation between two variables, line graphs for YoY growth, etc. Visualization can only be useful only if presented with a suitable graph.                                                                                                                                                                                                                   

Get feedback, test, and learn – 

Like everything else, our visualizations also will not be perfect the first time around. Create reliable feedback loops, Test, and correct.

And you will have a visualization that will make decision-making easy. As we see, whatever we want to ask from the data, Tableau has got us covered. The teams can look at their KPIs, metrics, look at the performance of their peers, region-wise and segment-wise performance, anything and everything that one can think of. Better feedback and pinpointing of the underlying problem mean improvement upon it. This is how Visualization helps in growing your business.

Final Thoughts 

We saw in this article how important it is to visualize your data, the ingredients, and the recipe for a great viz. Visualizations are helpful not just in a particular use case but over a wide range of topics. ‘Customer Stories’ edition on Tableau’s website features different use cases for a wide variety of customers.  

For example, Verizon used the Tableau COVID-19 data hub to see changes in service demand compared to last year and adjust resources accordingly. Sysco LABS, which used visualization to deliver insights for the sales team for their new e-commerce app or the state of Indiana in the US using visualization for better citizen engagement on matters of public policy, the use cases are innumerable.  

Therefore, every business needs to harness the power of visualization and speed up its growth. So now is the time to embrace data visualization and it will boost your company’s productivity almost immediately. 

About Viz-CoE:

With an intention to lead the way in exploring and adopting new technologies, tools, techniques, or practices in the area of visualization, RoundSqr has kick-started a new initiative called “Viz-CoE”, Visualization Center of Excellence. Contributions from our subject matter experts, clients, partners, industry leaders, colleagues, and interns through perspectives, training courses, success stories, and opinions bring this initiative to life.