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Data accuracy vendor boosts MDM data quality

Naveego's latest platform update introduces a new user interface that looks to make it easier for users to integrate different data sources while ensuring data quality.

Naveego's newest update, released Tuesday, expands the data integration capabilities of its data accuracy platform.

The data accuracy vendor's Complete Data Accuracy Platform is aimed at enabling users to get accurate data from one location to another so it can be used for data analytics.

In the platform update, the data accuracy vendor, based in Traverse City, Mich., improved data integration features and provided new compliance and security options for users. The Naveego platform also includes a master data management (MDM) capability for data quality and assurance.

Another key element of the Naveego update is an enhanced self-service-based model with a new user interface that enables users to complete tasks faster.

The new user interface will be particularly useful for organizations, said Mike Matchett, founder of the Small World Big Data consultancy.

"Implementing data quality and governance solutions usually requires big projects with lots of experts, custom scripting and time," he said.

Naveego is aiming to provide a different approach with data integration features from a cloud-oriented mindset, which is more aligned with simply subscribing to a service, Matchett said. He added that MDM systems have tended to be tuned for specific use cases, which isn't the direction that Naveego is taking, either.

Naveego data accuracy platform
Naveego's platform can capture different data sources and then monitor them all for accuracy.

"The best approach to data, and data consumption for analytics and machine learning is to integrate and fold in all sources of data that could be advantageous," Matchett said.

Instead of focusing only on large data center-style enterprise applications, newer platforms like Naveego aim for integrating and "mastering" data across hybrid cloud sources, data warehouses and data lakes to serve up quality data for more immediate use by end users in all capacities.  

The best approach to data, and data consumption for analytics and machine learning is to integrate and fold in all sources of data that could be advantageous.
Mike MatchettFounder, Small World Big Data

Naveego bringing data quality to data lakes for analytics

Naveego founder and CTO Derek Smith said Naveego is seeing increasing numbers of organizations treating data lakes like data warehouses. The challenge is that a data lake doesn't have the same data structure as a data warehouse.

To that end, the Naveego update now has enhanced extract, load and transform capabilities to improve data integration from data lakes and high-volume transactional workloads. The data integration is all done in a self-serve model with a no-code approach. Naveego has its own set of data connectors that tie into the change data capture mechanisms that are present in a given data source.

"We're able to provide even master data management in real time, where as soon as a change is made, it's delivered everywhere it needs to be right away," Smith said.

How Naveego data accuracy for MDM works

At the core of MDM is the promise that a "golden record" of data can be created and maintained that provides the most accurate and updated version of data. For Naveego, the MDM process starts with ensuring data quality, which is enabled via a profiling system that analyzes the data source and its structure. Accuracy is another core element of MDM, making sure that a given data set is not a duplicate or out of date.

The Naveego platform constantly compares data as it is being ingested as part of a data pipeline. Users can manually select which version of a given piece of data, such as a customer address, for example, is the most accurate. Going a step further, Smith noted that Naveego also pulls in third-party data sources to validate information, such as an address, with a verifiable provider.

"We really help the business to start to build up what that golden record means," Smith said. "Then we deliver it to the data lake, but we also deliver it back to the other sources so that way they can be consistent, because we believe that consistent data is accurate data."

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