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Global Data Governance

  1. Job Title – Company
  2. Job function (e.g., overall role, assigned tasks)
  3. Examples of projects (e.g., list the projects you worked on and what you accomplished)
  4. What you learned and how it relates to your major (e.g., describe what you learned from this experience in the context of specific courses)

For my summer internship, I had the opportunity to work at PepsiCo as a global data governance intern in their data analytics team. My overall job function was to ensure the availability, usability, and standardization of data when it came to our consumer products. I would highlight any issues of consistency in attributes and point out the errors that may have been computed to the IRI which is one of the marketing vendors providing the 2nd and 3rd party data sets for me to work with. My first and third projects in the company were looking at flat files with the IRI’s intern Mack to rectify any consistency and accuracy errors. I specifically looked at salty snacks and macro snacks. These files contained hundreds of thousands of data values and it was my job to make sure this data was valid and ready to be processed by our data engineering team. My second project was about our commercial cloud project where we validated SKUPOS and PDI data values about a high cone issue. High coming is when a family-sized product is sold one by one at an inflated price rather by the family-sized price leading consumers to pay for higher prices because of the vendor breaking apart the family-sized packages to sell individually to the consumer. I analyzed the UPC labels and data files to highlight and present any issues to our team when it came to the SKUPOs data values. These high cone issues were present when it came to the small mom-and-pop shops. Other than ensuring the validity of the data sets I accomplished a task in which I highlight a size miscoding on the IRI’s data values when it came to our salty snacks. Roughly 6% of the salty snacks across hundreds of thousands of products were classified improperly. PepsiCo could have made poor or inaccurate business decisions based on this data, as all the data values in the flat file are processed in a system called unify to calculate metrics. Particularly, PepsiCo could have miscomputed its volume share metric against competitors. Through this internship, I learned the concept of GDG (global data governance) and how it is the foundation of data analytics. Oddly enough, even as a TA for MIS 2502 Data Analytics, this is something that is not covered in the course even though it is essential for the synthesis of all data. I also learned how the company computes metrics and standardizes 2nd and 3rd-party data.

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