Poor Data Quality
Many organisations don’t realise the terrible state of their data. They have dirty data spread throughout their data sets, with inaccurate, incomplete and out-of-date information littering their ERP system and databases. Some common types of data errors include:
- Invalid, incomplete and missing information in place of essential details such as names, addresses, phone numbers and email addresses
- Illegal characters, spelling mistakes or incorrect information within the data fields
- Information in the wrong fields, i.e. phone numbers in the address field, emails instead of postcodes.
Your business decisions and sales effectiveness depend on clean, accurate data. Data cleansing is critical as it ensures information is consistent, standardised and uniform, in the right fields and uses only valid characters. Acclimation apply various cleansing routines according to each client’s requirements, and can also help to determine business rules for maintaining data quality in the future. A complete data cleansing process improves the condition of an organisation’s data in terms of:
- Errors and inconsistencies
- Secure data transfer and processing
- Duplicate record detection and golden record creation
- Best practice rules
- Support from an experienced consultant to explain the duplication results and what they mean for your organisation.