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How to take care of data quality?
Decide to implement Data Quality Management in your firm to deliver clean, trusted data so your projects meet your business objectives. Sometimes, the vast amount of customer data is located in different systems, along with possible information distortion, which leads to several or even dozens of versions of one customer. That makes your marketing campaign non-effective as you cannot deal with successful marketing without adequate data quality.
What is
data quality?
Ensure quality data in your company and keep data quality management procedures, that include measuring data quality, improving it constantly and delivering to your firm our monitoring of data status at the initial stage of its collection.
Complete data - lack of complete data put you at risk - for example, an apartment number in an address will prevent delivery.
Consistent data - no contradictory elements in the data, e.g. a street that does not exist in a given city will prevent delivery to the addressee.
Up-to-date data - when your data is not updated, an outdated address or addressee's name will prevent the shipment from reaching the correct addressee.
Standardized data - e.g. lack of standardized notation and Roman numerals will prevent the printing of a correct waybill.
Unique data - no duplicate data. If you duplicate addresses your addressee will receive the same shipment twice.
What are the key dividends of a data quality solution?
- Data discovery – you will learn more about your data and identify its problems.
- Ready-made data – quality rules guarantee for next of use for any data from any source
- Data quality transformations will enable you to integrate, clean, and standardize data, verify addresses and remove duplicates.
- Continuous monitoring of data will ensure quality data from the source systems.
- Analytics backed by artificial intelligence will automate and streamline the data quality management process.
- Detection of deficiencies at the initial data entry stage.
