Get in the Contact Zone

Blog Administrator | Analyzing Data, Analyzing Data Quality, Data Integration, Data Management, Data Quality, Data Steward, ETL, Global Data Quality | , , , ,

If you’re
looking for that perfect all-in-one solution that combines the power of easy
integration and Melissa’s full spectrum of data quality solutions, then you
need to get in the Zone – The
Contact Zone®.

Contact
Zone employs all the customer data management tools you’ll need to help provide
consistent, trusted, accurate data across the enterprise – all in one single
platform for effortless integration. 

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Meet Melissa: Global Intelligence

Blog Administrator | Analyzing Data, Analyzing Data Quality, Big Data, Data Cleansing, Data Enhancement, Data Enrichment, Data Governance, Data Integration, Data Management, Data Matching, Data Profiling, Data Quality, Data Warehouse | , , , , ,

Melissa
Data is officially now Melissa.

 

As
we welcome our 32nd year in business, we are excited to announce an important
change at Melissa Data. We’ve decided to drop the “Data” from our brand
identity. We are simply Melissa now.
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A 4-Step Plan to Improving Data Warehousing for Healthcare Organizations

Blog Administrator | Data Management | , ,

Many healthcare organizations find themselves coming across
the following problems caused by data quality: fraud, bad debt, billing
inefficiencies, and even life threatening issues that involve diagnosis and
prescribing care and real-time analytics.

On top of all that, healthcare organizations are attempting
to handle the increase in the amounts of data while transitioning from paper to
electronic health records.… Read More

Standardizing Classifications

Blog Administrator | Address Quality, Analyzing Data, Analyzing Data Quality, Data Governance, Data Management, Data Quality | , , , , ,

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?
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Data Quality Incident Management

Blog Administrator | Address Standardization, Data Integration, Data Management, Data Quality | , , , , ,

By David Loshin

The previous step in our transition from uncontrolled reactivity to being proactively engaged in managing data quality involved defining processes for identifying and evaluating data errors using standardized methods. Providing well-defined processes to data stewards and data quality analysts helps reduce any confusion around the appropriate steps to take when those commonly-occurring data failures are discovered in process.
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