Data cleaning is the process of preparing data for analysis by removing or modifying data that is incorrect, incomplete, irrelevant, duplicated, or improperly formatted.
But, it isn’t as simple as organizing some rows or erasing information to make space for new data. Data cleaning is a lot of muscle work. And there is a reason data cleaning is the most important step if you want to create a data-culture, let alone make airtight predictions.
The database cleanup process that SWEEP performs includes these tasks:
- Removal of Duplicates
- Fix Missing Data
- Parse Data into Complete Records
- Consolidate Lists into a Single Database
- Merge Data
- Purge Old Data
- Standardizing Your Data