Benefits of the Data Matching Process as a part of Data Quality Management
Data quality management is an essential aspect to avoid the issues that are caused by dirty data. Data cleansing and data quality services are types of measures that come into data quality management. Data matching that is a part of data quality services is a process that enables you to reduce data duplication and also helps you in enhancing the accuracy of data. As you record instances of data sets that are matched, you can decide about the duplicated records and take an action with respect to the source data. The process of data matching can be conducted solely or along with other data matching processes as well.
The benefits of data matching can be enlisted as follows:
- You can ensure the uniformity of the values that are equivalent but are entered in varied styles or formats.
- Matching data sets can match in an exact or an approximate way. In either case, you can validate the duplication pattern and decide on eliminating the duplicate data. You can also recognize which data sets have been validated and which are not.
- If you have two data sets that are matched, for example contact information of a customer, you can make out the reasons for duplication. For example, a single address is matched as it occurs twice due to some error in spelling. In that case, the erroneous part can be eliminated and the correct data can be retained. Thus data matching can bring out the causes that result in duplication of data and thus reduce the amount of dirty data.
- Data matching policies can be defined and redefined. If this is done through automation software, you can set various parameters depending on the type of data to be validated. The search parameters can be modified any time. You can also choose to re-index the data that has been matched.
- Thus data matching constitutes an important task as it helps to reduce the amount of dirty data and also helps to eliminate the factors that can lead to the generation of dirty data.