Validation, Standardization, and Correction: Tool or Process?

Blog Administrator | Address Check, Address Correction, Address Standardization, Address Validation, Data Enrichment, Data Governance, Data Integration, Data Management, Data Profiling, Data Quality | , , , , ,

By David Loshin

There are all sorts of tools associated with
address standardization, cleansing, and validation. As an example, the USPS
has a certification program for software vendors, referred to as CASS
(Coding Accuracy Support System)™ certification. According to their
website,

CASS enables the Postal Service™ to evaluate the accuracy of address matching software programs in the following areas:

(1) five-digit coding
(2) ZIP + 4/ delivery point (DP) coding
(3) carrier route coding
(4) DPV®
(5) DSF2®
(6) LACSLink®
(7) eLOT®
(8) RDI™ products

CASS allows vendors/mailers the opportunity to test their address-matching software packages and, after achieving a certain percentage of compliance, to be certified by the Postal Service.

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Synergizing the Process for Locations and Addresses

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

By David Loshin

I am currently working with a number of clients who are dealing with particularly thorny issues relating to location. While the business drivers are relatively diverse, there are some similarities across all scenarios, especially in the ways that location is managed from an enterprise perspective.
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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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Standardizing Your Approach to Monitoring the Quality of Data

Blog Administrator | Address Standardization, Analyzing Data, Data Cleansing, Data Integration, Data Management, Data Profiling, Data Quality | , , , , , , ,

By David Loshin

In my last post, I suggested three techniques for maturing your organizational approach to data quality management. The first recommendation was defining processes for evaluating errors when they are identified. These types of processes actually involve a few key techniques:

1) An approach to specifying data validity rules that can be
used to determine whether a data instance or record has an error.

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