Fortune 500 CPG Company Saves 200+ Hours Annually with Automated Dashboards
Customer's Challenge
A Fortune 500 consumer packaged goods company needed a series of dashboards built to visualize a multitude of quarterly reports. Unfortunately, the data lived across many poorly formatted spreadsheets and required excessive hours each week from analysts just to process the data from high-impact reports.
phData's Solution
phData migrated data from 20+ Excel connections to a centralized Snowflake Data Cloud source. The easy-to-access data was then used to create the necessary dashboards in Tableau, which were able to be updated automatically.
Results
Thanks to our analytics engineering services, phData’s analysts saved over 200 hours of manual processing a year. This ultimately opened time to uncover previously hidden insights from their data while reducing reporting errors and inconsistencies.
phData is excited to continue enhancing relationships between our clients and provide quick and successful analytical solutions.
The Full Story
Consolidating data from different factories is a challenging task, especially when you have more than 20 factories around the country that each have their own file template. At month’s end, the client had to gather and format data from all of its factory’s spreadsheets, Sharepoint files, and SAP Hana data.
This process required a large chunk of the business users’ time and was prone to errors due to copy/paste and formula use. phData’s team leveraged Alteryx to broker all input files and prepared a standardized output to Snowflake and a hyper file for Tableau. The process was scheduled for automatic refreshes and ended up saving more than 200 hours of work each year.
Why phData?
phData’s wide range of expertise on self-service analytic platforms initially attracted the client. The case was strengthened when phData’s expert Alteryx Artisans offered to deliver a solution within the required parameters with the already purchased resources.
Take the next step
with phData.
Are you spending countless human hours processing data? There’s a better way.
