You Can't Be Data-driven Without A Data Catalog

Enterprise wide Virtual Data Lake platform to power intelligent actions.

It’s repository of every type of data collected and catalogued in a single platform.

It deals with governance, discovery and analysis of data.

Platform for bankers, data scientists, researchers and analysts to access enterprise data for Analytics / processing.

Big Data and Machine Learning Technology:

Built using stack of advanced technologies involving Big Data (Hadoop and Spark), Elastic Search and Machin Learning based Analytics.

Centralized Search:

Provides a centralized search and discovery platform with the ability to aggregate data from disparate sources in a virtual data lake.It provides an abstraction layer for data consumers to access data in a consistent manner.

Integrates with a wide range of data sources:

Integrates with SharePoint, HDFS, AWS S3, FTP, MySQL and MongoDB. Future release will include adapters for other industry standard and client specific custom data sources.

Data mining, cataloging and analyzing solution:

It enables importing and indexing of metadata from disparate repositories in one place and organize them for faster access and discovery.

Secure and Entitled Access:

Platform designed to provide secured access to data based on users entitlements. Designed for both on premise and cloud deployment.

Virtual access to Data Sources:

Content can reside in original data stores or can be acquired and persisted in the lake. Data acquisition is managed and controlled through Jobs that are configured through web interface.

Petabytes Data, massive throughput:

Designed to scale to store and analyze petabyte-size content, trillions of objects and billions of messages/events in a day.

Graphical visualization of Sentiment and heat-map analytics of data:

Sentiment, entity extraction and heat-map analytics on the data in the lake using machine learning tools. Graphical visualizations are used to represent sentiment and heat-map data.