Power of Data Viz!

With this blog today, I want to talk about the importance of data visualizations and what it means to different business stakeholders. I’m no expert in data science nor have any statistical background but with this blog, I just want to share my journey of stepping into the big-data industry and how it has shaped my career.

It all started in the year 2015, when I took up the business intelligence course at Harvard as part of my degree requirements. Prior to this I only created some charts and graphs in excel or power point but wasn’t really aware that there were any specialized tools that were available in the market that could help businesses in making intelligent and data-driven decisions. A lot of these tools are very user-friendly and creating visualizations using them is merely like a drag and drop task when it comes to seeing and understanding the data. You definitely need an analytical eye in finding those patterns and making any tactical or strategic decisions but creation of these charts and graphs had never been so easy!

I’m happy that I started off my journey by learning with the most complex tool that’s available in the market called ‘Tableau’ because now the every other tool I come across is way simpler than this one:) My first dashboard that I created using this tool was a health monitoring dashboard for one of the most renowned hospitals in Massachusetts. The goal of this project was to create a framework that can help the healthcare professionals to not only draw some valuable insights from the past performances of their health monitoring system but also help them in making future predictions that could provide some decision guidance. The three main components of this framework were:

  •  Descriptive Analytics

  •  Predictive Analytics

  •  Prescriptive Analytics

Where the descriptive analytics helped the organization in identifying the trends and patterns of the problem as to what happened and why, the predictive analytics helped them in making an educated guess at the likely results. It’s more about guessing the future and useful in making the low complexity decisions. Prescriptive Analytics being the most powerful tool helped in solving more complex and time sensitive problems by applying computational sciences that typically involved machine learning or you may call mathematical programming to optimize the set of decisions for directing a given business situation. This dashboard helped the organization with improved operational activities and increased profitability. 

Although the Prescriptive Analytics was a proven most effective model even back in 2015, its usage by different businesses was only limited to ~10%. As per Gartner, this number is predicted to grow to 35% by the end of 2020 but that still doesn’t make it the most popular choice when it comes to business intelligence. And it should certainly not as data analytics is not considered to be a one-size-fits-all box strategy. In fact, what differentiates the best data scientist, is their ability to identify the kind of analytics that can be leveraged to benefit the business and help them develop the right metrics. And what is a good metrics?

A good metrics tells you a story, and they are best received when they tell a story about something that the stakeholders care about.

For different personas, this metrics can have different meanings.

For a Product Manager, this metrics is a key to develop the right features, at the right time and make sure they’re delivered to the right customer. It helps them in prioritization, measuring goals, defining success metrics and taking product strategic decisions.


For a Project Manager, metrics is everything! It’s an old cliché: What gets measured gets done! Regardless of the origin, the message is clear: measuring something gives you the information you need to verify that you actually achieve what you set out to do. It’s more about setting the project objectives and measuring its success criteria. Because every time, you miss that deadline or you add another resource to your project, you are increasing the cost of the budget, so it is very important to track the progress of your project.

For the Marketing Professionals, it’s all about measuring the performance to maximize the efficiency and improve the processes to increase the return on investments!


One very important thing to remember while creating any metrics is that the visuals should only show information that can be used either for operational, tactical or strategic decision making. If your numbers are too good to be true and are not adding any real value to your business, then they can’t provide you any actionable steps and is merely a vanity metrics!


Immediately after completing my BI course in late 2015, I got hired by Avention in Jan 2016 as a Product Manager for their Business Entity Data. And that was the time for me to brush up my SQL skills and get my hands dirty with some serious data mining and data processing techniques! I was given to lead the asia-pacific region and was responsible for analyzing all the raw data that we received from different vendors.  Two very important lessons that I learned here were: 1. As we are no longer living in an information-starved situation, the imprecision or messiness of the data is a positive feature and not a shortcoming. 2. 80% of the data scrubbing can be easily done with the analytical tools but the later needs human intervention. Hence, data science is a sensible integration of human knowledge and computer-based techniques to achieve what neither of them could achieve alone.


I wasn’t really involved in any data visualizations until Avention got acquired by D&B in 2017. And with this acquisition, I took a break from directly managing the products by moving to a more of a PM coaching role where I was required to train the PMs on the road-mapping, prioritization and other PM related work. As this role left me with some spare time during the day, I learned about this new tool called Microsoft PowerBi and started creating dashboards for my team. As I was the dedicated coach for the Global People Data Team, I got to work very closely with the data engineering, data innovation and the data compliance teams. 


My vision for the team was to create a one-stop view where we can see the data flowing through the entire lifecycle from every single endpoint. The only picture that I had in mind was similar to the dashboards that are used in the stock exchange market. I wanted to see every single progress made in real-time. Starting from sourcing this data from the third-party vendors to passing it via different stages like data ingestion, data cleaning & normalization, processing it with the trading system and making it available in final product. It had never been so easy to measure the growth geographically as well. The conversion funnel helped us in identifying so many gaps inside our own processes. By creating a data gateway we were also able to connect our reports to the production server that gave us access to the data in real-time. We had also setup alerts so that every time our trading system was down for more than 24hours, we received a notification that called for some action. And every single time our critical data points were moving up/down outside of the given threshold; we were the first ones to know the faults in our system before our customers or anybody else in the organization which was one of our main goals. To know our data better! From creating scrolling fun banners and making predictive charts to using a more interactive NLP (natural language processing) technique to query our data on-the-fly while presenting. And all this was done using Microsoft PowerBi! Along with this strategic dashboard, I created various operational dashboards too for measuring the teams sprint health and also a program level dashboard to track all the projects that were in progress. 


Worked on several projects at Harvard on customers onboarding, employee’s mentoring etc. and demonstrated a fully functional thesis too using this tool in my final semester. Lately, I have been working with various other data analytics tools like Looker and Amplitude but I can’t stress enough of how user-friendly Microsoft has been and why it has been my best experience so far! No doubt why it’s again rated as #1 by Gartner for the 13th consecutive year

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