Data Lake Management

Keep your data lake clean and find, analyze, curate, shape, enrich the right data to enable AI and analytics.

DvSum-Do you know what is in your lake?

Do you know what is in your lake?

Data lakes allow you to bring a lot more type and volume of data and from new sources that never existed in the enterprise data warehouse. However, that also makes having a catalog, definition, metadata about the data in the lake even more important. Leverage DvSum’s model mapping and business glossary to catalog all your data and establish a common definition of data for various analytics needs from the lake.

Filter data before it enters the lake

DvSum data preparation platform lets you define powerful business and technical filter criteria. These filters allow you to ensure that the data entering into your lake is as clean as possible.

DvSum-Filter data before it enters the lake
DvSum-Keep the data lake clean

Keep the data lake clean

Just like with enterprise data, Data Lakes also start becoming dirty over time. The difference is that the volume of data that may be dirty, old or not relevant  is significantly higher and can result in higher  noise in your predictive analytics efforts. DvSum rules engine deployed as a production workflow acts like a self-driving submarine that continually identifies, scrubs and keeps the lake clean and relevant.

Sandbox it in DvSum Cluster. Deploy in your own

Use the DvSum  connectors for Big Data to connect and automatically catalog your lake inventory, or drop in files directly into DvSum AWS S3 to define transformation steps and export your data for downstream needs. Re-use the transform script to run with new data anytime. Or deploy the transform as a production application to run within your own Data Lake.

DvSum data platform possibility illustration

Schedule 15min discovery call with DvSum

We'd love to discuss how we can help you get more value out of your data and show you our platform and technology.