How identifying the right tool for your “What-If analysis” determines its success

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How identifying the right tool for your “What-If analysis” determines its success.

June 7, 2022

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Transition from Traditional BI to Modern BI: 

In today’s digital era of exponentially growing data, as significant and process oriented it is to extract the information from data, equally important is the process of visualizing those insights. The value of the insights gathered from the data processing and analyzing is justified when it is visualized in the right way. There is a shift happening from the traditional BI to modern BI which looks for a digital transformation with sophisticated features in an easy-to-use integrated BI environment. It focuses more on the accessibility and flexibility aspects irrespective of where the data comes from and where the analytics is viewed, all this while maintaining the data governance and the data security is where the BI is heading. 

When it comes to right way of visualizing, the best thing to do is simulating and playing with the visualization and its underlying data.  Many tools provide this feature of interaction with the visuals in form of filters, tooltips, parameter selection, on click filters and many more options. But there are very few tools that emphasize on recording that input from interaction by the user and reflecting that on the view as soon as its refreshed. 

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How about having the capability to give in your input and have some KPI’s get calculated on the fly based off those inputs without having to go to a new tool or new data source? How about looking at the current inventory status and see what would it look like if few orders are placed for certain items or what if the demand spikes?  

What-if Dashboards, the need of the hour: 

Having that visualization where you can simulate these situations is the need of the hour. All these are what-if situations which are very useful in being proactive.  What-if analysis has been the key to making informed decisions/actions reducing uncertainty. It keeps us prepared for the alternative scenarios that could occur and to know what and how it would impact. A tool that lets you do this with a complete customization to your case is a bliss. 

We have a way to achieve this through customized application development currently with lot of thought (Money as well!) to put into its execution with the traditional approach. With things to worry about the application development, its security, reliability, and infrastructure required like server to host the application amongst the others makes you forgo the whole idea. 

Domo, the futuristic BI tool: 

Domo has built the quintessential BI platform, one that is empowering businesses and the business users with the self-serviced analytics with a focus on embracing the modern BI perspective. It is working towards the same goals of accessibility and flexibility by integrating the data ecosystems in a business for customers as well as partners letting them make most of their data and have a data experience to commercialize it. Domo also has out of the box capabilities in terms of visualizations along with data cleaning and preprocessing. 

Domo has featured the custom application development which allows you get an input, host the application based on this data and store the interaction data all within the Domo environment. With the help of the APIs, we can not only host a view in Domo but also create a customized view altogether.  

We the team here at Indium have worked on creating 15+ custom apps for the clients to help them do the scenario-based analysis. The apps are visualization built that take inputs in terms of event information to be noted in the dataset and are expected to be merged with the dataset which is input to the view in the backend to reflect the new KPI values based on the input. 

As given in the architecture below, within the domo environment we have the dataset which is an input to the visualization and is also connected with the AppDb which stores all the interactions from the user given through the visualization. These interactions are pushed in the input dataset through the recursive ETL flows. These ETLs are set to run whenever there is an entry of an input from the user in the AppDb to reflect it on the Dashboard in real-time. 

Given the API connectors of Domo it is an easy task to access, read and writeback data into/from the Domo ecosystem. These API calls can be triggered from any user interaction made on the visualization. All the data governance rules are intact in implementing these API calls to read the data from the datasets. This gives flexibility to the user to give in their inputs and see the visualization change on the fly based of their inputs. The best part is all this can be achieved without having to worry about the infrastructure for application hosting.

Below is a dashboard that is showing the approval status of the invoices in a company. When a user clicks on the Approve button that action is immediately tracked back to the input dataset of the view and the numbers on the dashboard are changed accordingly. Also, the security is maintained by allowing on the intended user to approve certain invoice. We can further restrict the view to show only the invoices a user is expected to see. It helps us give the real-time view of the statuses for invoices.

Conclusion:

Embracing the Modern Business intelligence service’s evolution is the way to up the game in analytics. With Indium and Domo, we can help you achieve your analytics goals with a futuristic approach and help you utilize the data asset to the fullest.


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