The client is one of the giant retailers in the US that offers a variety of food supplies, and services. They have a strong
reputation for providing high-quality products and outstanding customer service.
Queried a data pipeline to transform and load raw data from various platforms into the targeted tables in Snowflake.
Built multiple bar graphs to project the monthly and yearly CPU values between both the fiscal year for each variable.
Added week, month, and a variable filter to show the desired CPU values based on the user selection.
Created multiple single-value card graphs to show this year’s vs. last year’s weekly, monthly, and yearly CPU values as well as calculated WoW, MoM, and YoY % change values for the selected variable.
Created an overview table to show the CPU values for both fiscal years for all the variables.
Created a line chart to project the actual as well as the forecasted values for the current fiscal year and actual values for the previous fiscal year.
Added a variable filter to showcase the actual and estimated values for both fiscal years based on the user-selected variable.
60% reduction in runtime for transition from manual data load in excel to looker database.
Dashboards provide valuable insights about the data behavior and market changes which helps to take better decisions.
Showcasing multiple graphs and charts as a single view which helps the users to understand data trend-lines quickly and efficiently.
Dashboards can download into different formats and it can share to stakeholders, users, analyst via email or in group chats.