At IT Partners in the Gies College of Business, we’ve been tackling the challenge of standardizing company names for some time now. As we process data from various sources, we encounter a wide range of discrepancies, inconsistencies, and duplications in company name formatting and hierarchies. Currently, our efforts to clean and standardize these names are largely manual, requiring extensive time and resources. With the ever-growing amount of data, we are seeking a more automated, scalable solution.

The primary goal of this session is to gather data professionals from across campus who are facing similar challenges in handling messy, unstructured data. We aim to foster a community of practice where participants can share their approaches, tools, and solutions for company name standardization.

Goals of the session:
– Explore different methods, tools, and strategies for automating the process of company name standardization.
– Learn from others on campus who are also grappling with this problem and discuss potential collaborative approaches.
– Identify best practices and opportunities to align data practices across departments, improving data quality and efficiency.
– Lay the groundwork for building a long-term community of practice focused on data standardization and related challenges.

About this event:

Presenters: 

Krista DeLeeuw, Data Analyst, IT Partners, Gies College of Business
Marian Pan, Data Analyst, IT Partners, Gies College of Business
Lauren Gray, Data Analyst, IT Partners, Gies College of Business
Patrick Nowlan, Manager of External and Constituent Data, IT Partners, Gies College of Business

Track:

Software, Security, Data, and DevOps

Experience Needed:

Intermediate

Learning Outcome:

Maximum Capacity:

No maximum capacity

Additional Keywords:

Data standardization, Data quality management, Employer engagement, Placement

Time:

10 am November 12