Simplifying Processes with Data and Analytics
The X Factor
Editor's Note: The X Factor is a blog series featuring data rockstars and their everyday challenges and solutions.
This blog features Sambit Das, Workday Data Test Lead, The Salvation Army. Sambit shares his insights into simplifying processes with data and analytics.
While data and analytics are the focal point of Sambit Das’ role as a Workday data test lead for The Salvation Army, one of the world’s largest social welfare organizations with more than 1,650,000 members working in over 128 countries, his passion for solving complex challenges with data and analytics extends beyond work hours.
"I’m a data scientist outside of work,” Das says. “There are so many pressing issues our world faces today that I believe can be solved using data. Healthcare, research and development, the global workforce, diversity inclusion, the list goes on."
When Das was tasked with the migration of over 200,000 rows of data for 10,000 workers from multiple legacy systems into Workday, he knew he was in for a daunting task at hand. He noticed that the state of systems and data flow at The Salvation Army was complex with no single source of truth, and the volume of historical data coming in from disparate systems was overwhelming.
"Creating organizational reports such as national level workforce reporting, tracking integrity checks, and training compliance data was extremely difficult and time-consuming."
He recognized the need for a better way to automate and optimize this challenging process to make the migration run smoother.
"We needed a solution that could automate our data migration and transformation processes in an easy and repeatable way."
A solution that led to unprecedented time savings
Utilizing his vast arsenal of skills in data and analytics (along with the Alteryx analytics platform), Das was able to develop a repeatable and automated data migration process that helped generate massive time savings in manual effort, and enabled his team to work through the data migration process on a much quicker timeline.
The next task for Das and his team will be phase two of the initiative, which will involve migrating 30,000-40,000 worker and volunteer data into Workday and utilizing predictive analytics and assisted modeling to tackle other initiatives.
Das’ “X Factor”?
Putting data to work for him and his team by utilizing all resources available.
"The data we are working with is huge across the organization,” Das says. "So, it will be important to use that culture of analytics we are slowly but surely creating here."