SDS 487: Fixing Dirty Data — with Susan Walsh

COAT System

Susan Walsh introduces her COAT system, a framework for maintaining high-quality data. COAT stands for Consistent, Organized, Accurate, and Trustworthy, emphasizing the need for uniform terminology and organized data structures. "Data maintenance is really important as well," Susan notes, highlighting the necessity of ongoing data management 1. She stresses that organizations should take responsibility for their data, treating it as a valuable asset rather than outsourcing its management 2.

   

Classification Techniques

Susan and Jon discuss effective data classification techniques, particularly in procurement. Susan uses Omniscope, a tool combining data modeling, ETL, and visualization, to classify and normalize data efficiently 3. She emphasizes the importance of understanding the data before applying semi-automated processes, as this ensures accuracy and saves time in the long run. "It's not even that you save so much time in the long run because you're not spending so much time fixing things and figuring out where it's gone wrong," Susan explains 4.

   

Data Quality

Maintaining high data quality is crucial for businesses to save money and make informed decisions. Susan highlights common issues like misspelled supplier names and the need for precise data classification 5. She shares that clean procurement data can significantly impact a company's financial health and decision-making capabilities. "Having clean procurement data can save businesses money and enable better decision making," Jon adds, underscoring the value of data quality 6.