Data is becoming ever more important to organizations that do heavy customer service and outreach, yet the quality of that data often is poor. Whether it’s users intentionally filling fields with garbage, or the user’s lack of understanding of how the system wants an address filled out, companies find that much of their outbound communication is missing the mark.

To help companies deal with these issues, data quality software provider Melissa has announced the addition of a Profiler tool to Unison by Melissa, its customer data platform. Profiler brings to Unison a wide array of metrics and statistics to help users identify any potential issues in their data pipelines.

The Unison platform already features field verification, such as name, address, email and phone field, along with matching and geocoding. Profiler delivers an easy-to-use interface for users to make and configure their projects, and then lets users view the results in infographics, which even non-data professionals like business managers can understand.

“Unison provides an automation solution for technologists that standardizes the process and gives data stewards a solution for cleansing, validation, enrichment, and data integration without having to be programmers,” explained Greg Brown, vice president of marketing at Melissa Global Intelligence. “It’s a complete data quality hub with a simple point and click interface and ability to import or export to many popular data formats and flat files.”

The Profiler Object provides statistics around things such as duplicate counts, pattern and word analysis, data type mismatches, and others. Unison leverages Profiler to create infographics of the data points, and users can drill down to the particular statistics that interest them, which provides highlighted cells that can help the user identify data issues that need to be corrected.

Profiler also provides data type interpretations to analyzing columns, with options to control what statistics and numbers are crunched during profiling analysis, according to Melissa.

Further, Unison lets users compare the results of different projects in a side-by-side view, which can help users identify changes between runs, and to get a greater understanding of how the data is progressing.

A guided wizard helps users quickly and easily create data analysis projects, including private projects that don’t need to be shared, with naming and configuring projects easily.

“Organizations receive and transmit voluminous data on a daily basis for business critical processes. And, that data needs to be validated and cleansed before loading into data warehouse environments,” Brown said. “But it’s hard because the data often comes in unformatted, or in unexpected formats, and has other inaccuracies. How do we get the best of both worlds? Have developers build a system to support the organization while providing data stewards the flexibility to lookup, validate, and cleanse data prior to the production load without having to have the deep programming knowledge of the technical team.”