How can MDM Strategies Smoothen Supply Chain Management?

Melissa AU Team | Master Data Management | , , , ,

Data quality is critical to supply chain performance. In turn, this affects customer experiences and the organization’s growth. As sales volumes and marketing channels increase, supply chain professionals must be able to manage all the various data assets such as product data, customer data, vendor data, etc. and keep it complete, consistent, coherent and compatible. This is where Master Data Management can play a critical role.

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Customer Data Platform (CDP) vs Master Data Management (MDM)

Melissa AU Team | Customer Data Platform, Master Data Management | , , , , ,

There’s no doubt about it – the key to retaining customers isn’t about fighting price wars, it’s offering them the best experience possible. Customers like being wooed and to do this, the right way, businesses need to understand their customers. This is why customer data is so important. You need to know what is in your customer’s shopping cart to send them reminder emails, you need to understand their demographic profile to personalize their landing page, and so on.… Read More

MDM – Secure, Fast and Hassle-Free with Unison

Author | Data Quality, MDM, Unison | , , , , , , , , ,

Automated data quality routines, lightning fast processing (50 million records per hour), and no programming expertise required for master data management? Unison has you covered. It unifies all of Melissa’s data cleansing technologies through a straightforward, modern and powerful user interface without sacrificing speed or security. Explore what makes Unison so unique from other platforms and how it was designed with data stewards in mind.… Read More

Performance Scalability

Blog Administrator | Address Quality, Analyzing Data, Analyzing Data Quality, Data Integration, Data Management, Data Matching, Data Quality, Duplicate Elimination, MDM | , , , ,

By David Loshin

In my last post I noted that there is a growing need for continuous entity identification and identity resolution as part of the information architecture for most businesses, and that the need for these tools is only growing in proportion to the types and volumes of data that are absorbed from different sources and analyzed.

While I have discussed the methods used for parsing, standardization, and matching is past blog series, one thing I alluded to a few notes back was the need for increased performance of these methods as the data volumes grow.… Read More