Robust Scientific Approach for Impeccable Data Quality
What we did:
Developed advanced algorithms for data analysis and splitting the data into clusters.
Minimized time needed for optimal algorithm performance considering database inactivity requirements imposed by the business.
Conducted a series of continued tests on provided datasets for each algorithm modification for evaluation purposes.
Managed a complex interactive algorithm development and testing process consisting of many prolonged iterations.
Enabled the client to clean up a massive database of 10 million entries, remove duplicates, and fix data inaccuracies.
Equipped the business with a long-term data cleaning solution to process existing and new entries.