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.

Scattered Data, Obscure Insights

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:

  • Duplicated data with additional cleaning and storage costs
  • Legacy rule-based Extract, Transform, and Load systems
  • Sprawling data infrastructure is difficult to manage and govern
  • Crucial data is siloed and unfit to be processed for critical insights
  • Multiple data features with often the same data, costing dearly for storage and retrieval
  • Siloed systems for functions working on the same data

Considering that data is the backbone that businesses must base their decisions on, the data management system must be robust, flexible, and unimpeachable.

ML-driven Master Data Management

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.