One of the primary challenges organizations of all sizes regularly now face is the amount of data they need to manage across various silos of applications running on-premises and in the cloud. Much of that data is identical in that it refers to some aspect of a relationship a business has with a customer. But just because that data is identical doesn’t mean it is uniform. Data, for example, relating to company names or individual working at a specific company can have been rendered multiple ways by different individuals.
Naveego this week updated its master data management (MDM) cloud service to make it simpler to identify and resolve that issue across multiple applications running on-premises or in the cloud. The latest release of the Naveego Data Quality System (DQS) makes it possible to do so, for example, between an internal database and a software-as-a-service (SaaS) application being employed to manage customer records.
Other new capabilities in this release include the ability to use SQL to address and validate any type of data set, support for multiple types of Big Data, templates for checking data quality, and a dashboard through which IT organizations can monitor the health of their data on an ongoing basis.
Naveego CEO Derek Smith says in contrast to rival MDM services that rely mainly on application programming interfaces (APIs) to access data, the Naveego approach allows organizations to employ SQL commands.
“We bring it back to SQL because that’s the skill people have,” says Smith. “Most business users don’t know how to use an API. Naveego presents everything as a table.”
The result, says Smith, is a much easier way to maintain a single golden record of the truth concerning any given set of data.
As the number and types of applications continue to proliferate inside and out of the cloud, MDM becomes a bigger requirement. Not every organization engages in MDM as much as it should. But to one degree or another, most of them will need to address data quality issues to a much greater degree, whether they like or not.
