Organised and well-structured data is key to better decision-making, maximising output and efficiency, and exceptional customer experiences.
Improve analytics and decision-making
Leverage technology investments
Reduce costs for data storage and management
Data cleaning validates, reformats, updates and enhances business information to make it more usable and valuable. Some common data-cleaning processes include:
ADDRESS CLEANING
Matching addresses to postal address files lets us account for variations in the way people fill out forms. We can standardise formats, verify information like gender, addresses, phone numbers and more, and flag customers who meet certain criteria.
DE-DUPINGDe-duping is essential if you’re merging data from across departments, locations and systems. This intelligent process automatically finds likely matches, not just identical entries to create and maintain a single view of customers.
MATCHINGMatching arranges your data into groups based on set criteria. For example, it will group people who live together by matching on address data or identify likely duplicates before a merge. This process makes use of data more efficient and allows cross-selling and consolidation.
