Data profiling, data integration, and data quality are considered as the three important pillars of master data management as they work together to produce master and reference data based on the perfect set of rules and in the result we got the business with a high level of enterprise data and information management maturity. This defined data meet the determined level of quality and resides in the appropriate master data management MDM space. But the question here is how to gain the high quality master data? But, prior to integrating the data quality tool you need to identify your business issues and need to establish a strategic MDM plan.
Explore the Set of Attributes You Need to Follow While Creating MDM Plan:
* Figure out the business problems that MDM will address in future.
* Define critical metrics for data of your organization.
* Link the metrics to business issues for fetching the best result.
* Measure results and quantify improvements
* Communication is the source of key here, discuss the results and improvements across the enterprise
* Set your budget and set for next year.
Integration of Master Data Management MDM with Data Quality and its Respective Outcomes:
With emerging and open source data quality tools you can do significant data quality work for your organization and fetch the amazing outcomes. Let’ find out here the aspects of this integration-
* Make sure that your MDM program includes data quality management practices with the right data quality tools. To integrate MDM with data quality you need a good DQ tool and ensure that your data quality tool has no set of limitation, if have then, you need to enlarge it based on the organization.
* Emphasize the need of the organization to perform data quality management task on a regular basis and consider all the data it especially the master data.
* Enrich and uphold a data quality practice that includes master data, employed by experienced and organized data quality specialists.
* Perform the standard data profiling of master data using the proper tools and report the results, establishing a baseline for data quality.
* Use MDM hub for clean master data by implementing the rules.
In order to fetch the best and organized outcome one should lay emphasis on culminating these points in your business’s MDM strategy and need to integrate the data quality tool. It’s imperative that data quality measures the related workflows for the organization should be incorporated in a sophisticated manner. Regardless of other sources, integrating data quality with master data management MDM can be the best option.