Data Cleansing for Regulatory Department
ADAMA
Background
Within the Regulatory department, challenges were identified in managing and ensuring the reliability of licensing data in the system, affecting the ability to work with the data accurately and efficiently.
Main Challenges
-
Missing critical information in over 60,000 regulatory records
-
Lack of consistency in data structure and classification
-
Difficulty in managing, working with, and controlling data completeness
-
Difficulty navigating licensing records
Objective
To improve data quality and completeness in the system, enabling efficient management and control of regulatory records.
My Role
-
Leading the data cleansing project end-to-end
-
Analyzing data and identifying gaps in the system
-
Building a management tool to track progress
-
Managing work with internal teams and an external vendor
What I Did in Practice
-
Conducted comprehensive data analysis to identify gaps in regulatory records
-
Mapped and categorized types of missing information
-
Built a dashboard for managing and tracking data gaps
-
Defined requirements and wrote a requirements document
-
Distributed work between an internal team and an external company
-
Managed and monitored ongoing data completion
-
Ensured data quality and completeness throughout the process
Outcome
-
Significant improvement in data quality and completeness
-
Full transparency on data status and existing gaps
-
Improved ability to manage and control regulatory records
-
Established a structured process for completing missing data
My Unique Contribution
I led a large-scale data improvement process that combined analytical work, operational management, and cross-functional coordination. By identifying data gaps, structuring the process, and creating a clear tracking mechanism, I transformed a complex data challenge into a manageable and measurable workflow that improved visibility, control, and reliability across the department.