Melissa Data and Semarchy Partner to Integrate Data Quality and Master Data Management

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Melissa Data Enrichers Enable Clean, Global Contact Data for Semarchy Users; Webinar Demonstrates Best of Breed Strategy for Fast, Optimized MDM Operations

Rancho Santa Margarita, CALIF – November 12, 2014 – Melissa Data, a leading provider of contact data quality and data integration solutions, today formally announced its partnership with Semarchy, a developer of innovative Evolutionary Master Data Management (MDM) software and solutions.… Read More

Data is Born in Business Processes

Melissa Team | Analyzing Data, Analyzing Data Quality, Data Governance, Data Management, Data Quality | ,

By Elliot King

One of the most critical factors affecting the health of an organization is the relationship between business processes and the IT infrastructure. Data is created through businesses processes and the ways that these operations are designed and implemented have an enormous impact on the quality of the data, from acquisition through application, and retention. In short, corporate business processes generate the data on which companies rely.
… Read More

Standardizing Classifications

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By David Loshin

In the most recent post, we posed a straightforward problem: if we have a reporting or analytical objective that depends on using a dimension for classification, what happens when two different value domains are presumed to map to the same conceptual domain?

More concretely, the example we used was mapping individuals to their car
purchase preferences, but different applications used different car
classifications that did not share the same number of values and the value sets
did not directly map in a one-to-one manner.… Read More

Customer Centricity and Location Characteristics

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By David Loshin

In my last set of posts I began to examine the integration of the concept of “customer centricity” into business processes, starting with the ability to uniquely differentiate individuals in relation to their “contact-based” identifying characteristics, such as street address and telephone number.

Interestingly, from one part of the discussion, we could draw a conclusion that
due to the lack of prescience regarding the many different methods of contact
that exist today, a large number of application data models are insufficiently
designed to accommodate a comprehensive capture of the different ways to
interact with a customer.… Read More

Just Grow Up

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By Elliot King

When it comes to data quality, so many companies need a change of attitude–or to put it bluntly, they just need to grow up. Too often, organizations approach data quality reactively, addressing their efforts to fixing what they discover as broken as quickly as possible. A proactive approach is generally more effective. In this perspective, data is viewed as a strategic asset and data quality is seen as a strategic initiative rather than a cost.
… Read More