Compare DataBuck vs. Exmon

Big Data Quality must always be verified to ensure that data is safe, accurate, and complete. Data is moved through multiple IT platforms or stored in Data Lakes. The Big Data Challenge: Data often loses its trustworthiness because of (i) Undiscovered errors in incoming data (iii). Multiple data sources that get out-of-synchrony over time (iii). Structural changes to data in downstream processes not expected downstream and (iv) multiple IT platforms (Hadoop DW, Cloud). Unexpected errors can occur when data moves between systems, such as from a Data Warehouse to a Hadoop environment, NoSQL database, or the Cloud. Data can change unexpectedly due to poor processes, ad-hoc data policies, poor data storage and control, and lack of control over certain data sources (e.g., external providers). DataBuck is an autonomous, self-learning, Big Data Quality validation tool and Data Matching tool.

Our solutions monitor data 24 hours a day to detect any potential problems in the quality of data and its integration into other internal systems. This ensures that your bottom line will not be affected in any way. Verify that your data is accurate before it is transferred or shared among your systems. You'll be notified if something is not right and the data pipeline will be halted until it's resolved. Our data solutions are tailored to your industry and region to ensure regulatory compliance. Our customers are empowered to gain greater control of their data sets when we show them how easy it is to measure and meet data goals and requirements by leveraging our user interface.