MIOsoft Recognized in Gartner Critical Capabilities for Data Quality Tools

MADISON, Wis., Jan. 14, 2016 /PRNewswire/ -- MIOsoft received the highest score in 4 of 6 use cases evaluated in Gartner, Inc.'s Critical Capabilities for Data Quality Tools report,* MIOsoft announced today. Use cases in which MIOsoft received the highest score of all vendors rated are:

• Big Data & Analytics
• Data Migration
• Information Governance Initiatives
• Master Data Management

This is the second time in a row that MIOsoft has received the highest score in Data Migration and Information Governance Initiatives in this report.

MIOsoft received the second-highest score of all vendors rated in the remaining 2 use cases:

• Data Integration
• Operational/Transactional Data Quality

The December 2015 report evaluated MIOsoft based on MIOvantage, its data quality platform.

"One of our main goals with MIOvantage is to rescue companies that have spent a lot of time and effort trying unsuccessfully to force data quality solutions to meet their specific needs," said Jordan Barrette, MIOsoft's chief operating officer.

When a company embarks on a data quality initiative, Barrette explained, there are several major factors that can vary widely, even between organizations in the same industry. A data quality solution must account for the systems the data is currently located in, the systems the final data must be sent to, and the type, format, and structure of the data that the company has, among other variables.

"Realistically, you can't build a data quality solution that, directly out of the box, effectively addresses each of these factors for every possible customer," said Barrette. "Especially once you get into the true big data verticals like telecommunication, healthcare, and government, where there are a lot of custom and legacy systems."

Overreliance on out-of-the-box solutions, according to Barrette, is one reason why organizations can struggle significantly with data quality. Workarounds to address gaps in and changes to a standardized solution can become unsustainable over time. Frequently, organizations are then forced to choose whether to attempt to maintain the partial solution, or whether to change the business to reflect the technology's capabilities.

"For truly effective data quality, you have to embrace an organization's unique factors and make sure they're part of the solution from the start," said Barrette. "That's why we built MIOvantage to have robust tools that are innately flexible. We expect our customers to have unique needs, and designed our technology so we can deliver a complete data quality solution that meets those needs.

"We believe that our scores in the Critical Capabilities for Data Quality Tools and our positioning as a Visionary in Gartner's recent Magic Quadrant for Data Quality Tools** validates how effective our approach has been for our customers."

Disclaimer

Gartner does not endorse any vendor, product or service depicted in its research publications, and does not advise technology users to select only those vendors with the highest ratings or other designation. Gartner research publications consist of the opinions of Gartner's research organization and should not be construed as statements of fact. Gartner disclaims all warranties, expressed or implied, with respect to this research, including any warranties of merchantability or fitness for a particular purpose.

About MIOsoft

MIOsoft turns raw data into meaningful, actionable information. Since its founding in 1998, MIOsoft's technology has helped organizations of various scales—from startup companies to Global 2000 enterprises—solve their biggest data quality and analytics challenges. MIOsoft has a worldwide presence through MIOsoft Deutschland GmbH in Hamburg, Germany and MIOsoft (Beijing) Corporation in Beijing, China.

For more information, visit www.miosoft.com, or contact:
Lori Herrick
MIOsoft Corporation
[email protected]
608-210-1171

*Gartner Critical Capabilities for Data Quality Tools: Ted Friedman, Saul Judah, 18 December 2015.
** Gartner Magic Quadrant for Data Quality Tools: Saul Judah, Ted Friedman. 18 November 2015.

SOURCE MIOsoft Corporation

Related Links

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