Streamline your enterprise data in real time into de-duplicated single source of truth, reducing time and effort-intensive data management and granting business the time to drive high-value innovation.
Enterprises grapple with various disconnected data networks and diverse data storage platforms which let valuable insights slip through the gaps between them. As businesses strive to become data-driven, such scattered data can pose major challenges:
Considering that data is the backbone that businesses must base their decisions on, the data management system must be robust, flexible, and unimpeachable.
InfoVision’s DataMink, developed at our innovation lab- Digit7, helps enterprises develop the data integrity required to create a culture of smart decision-making. DataMink is an AI-enabled, self-learning platform that quietly runs Edge-deployed ML models in the background, eliminating data redundancies and managing data through self-evolving rules.
Replacing legacy ETL and rule-based engines with ML-enabled DataMink has clear advantages:
DataMink is one of the few platforms in the market capable of merging data across two or more different database types such as SQL and NoSQL.
Improves compliance through single source of truth, facilitating better decisions.
Self-learning ML models to perform legacy ETL operations and deal with new data formats intuitively.
Automated data de-duplication, database merging, schema mapping, cleansing.
Train multiple models multiple times, with different parameters with DataMink.
Access the DataMink dashboard through a web-based UI securely and easily.
DataMink is cloud-native, platform-agnostic and is scalable using Docker images.
Data visualization that helps practitioners view data in ways that highlight the insights.
DataMink can be readily deployed with your platforms through an API.
