NO CODE LIKE FOR LIKE ANALYSIS
According to Gopal Krishnamurthy, the founder of Inforiver, less than 10% of PowerBI users master DAX, M-scripts and the other tools that are key to maximize the amount of insight one can produce from PowerBI. A similar logic applies to Tableau.
As a result, an IT analyst will generally build the dashboard for the end user. This means that the dashboard is a canned structured analysis that limits the end user's exploration to the path that was defined by the content creator.
This keeps users tied to Excel and reduces the adoption of PowerBI.
Since today is mostly different from yesterday, the end user will often need an unstructured exploratory analysis approach to uncover new insights. The Inforiver no code PowerBI plugin empowers such an approach.
Inforiver is IBCS certified, and therefore the user does not have to reinvent the wheel of chart design. IBCS is a charting standard that defines a set of rules that make charts easier to understand and denser of information.
'Mparanza is built on a similar premise, even though it is not a dashboarding tool and has nothing to do with PowerBI.
'Mparanza is limited to sales and margin analysis and requires a flat tidy file in excel or csv format.
From there on, however, a user using 'Mparanza will be able to generate a complete set of charts in a format inspired by IBCS, with no need of coding or writing Excel macros. 'Mparanza also runs ABC analysis, commonality analysis, like-for-like analysis, cohort analysis and variance analysis out of the box.
Chart parameters can be intuitively adjusted to the objective of the analysis. Plotting a new chart takes a few seconds.
This is an example of a no code like-for-like product analysis for an imaginary retailer. It was completed in less than fifteen minutes.
The top right chart shows total yearly sales. The top center chart shows like-for-like sales for products sold in the last and previous year. The top left chart shows like-for-like sales for products sold in all four years.
The bottom left chart shows the average gross margin per product for all products, the bottom center chart shows the average gross margin per product for products sold in the last and previous year. The bottom right chart shows the average gross margin per product for the products sold across the whole period.
You can show different metrics, such as % margin, or run the like-for-like analysis by shop or by client, by simply changing a drop down menu choice.