Data Management
Data Governance, Data Catalogs, Data Lineage
Empower Your Business with Robust Data Governance and Management. Tackle the challenges of data security head-on with the help of a Data Catalog.
Discover what data you have, who's using it, and how to protect it. With metadata mapping, lineage relationships, and data masking, you'll have full control of your data ecosystem.
Bridge the gap with metadata and develop a comprehensive business ontology to stay ahead of the game.
EXPERT DATA ANALYTICS AND AI
Data Governance
We assist you in governing your data by providing information about its sources, schemas, processes involved in reading the data, data classification, data transformation undertaken, when the data was last updated, and any restrictions placed on the data. According to the explanation above, Data Governance enables you to comprehend your metadata, allowing you to make and execute appropriate actions when required.
Data Classification
We enable you to dynamically create classifications such as PII, EXPIRES ON, DATA QUALITY, and SENSITIVE. Attributes can be included in classifications, such as the expiry date attribute in the EXPIRES ON classification. Entities can be assigned to multiple classifications, making discovery and security enforcement easier. Classification propagation via lineage - ensures that classifications follow the data as it goes through various processing stages.
Data Catalog
Data Catalogs are one of the key components we provide as part of our data projects. Data Catalogs provide our customers with a unified, in-depth view of how all of their data is stored at any given time, assisting them in understanding the type of data they have, who is viewing or moving the data, and what the data being moved is used for.
Data Search/Discovery
we implement intuitive UI to search entities by type, classification, attribute value or free-text Rich REST APIs to search by complex criteria SQL like query language to search entities - Domain Specific Language (DSL)
Non Structured Data
In today's hyperconnected world, valuable data is constantly flowing across operational systems, and customers struggle to report this data due to a lack of appropriate technology and an over-reliance on manual data handling. We use data engineering technologies to collect, store, and analyze data from various sources, including social media, customer surveys, and other touchpoints.
Data Security & Data Masking
Fine grained security for metadata access, enabling controls on access to entity instances and operations like add/update/remove classifications Integration with Apache Ranger enables authorization/data-masking on data access based on classifications associated with entities in Apache Atlas. For example: who can access data classified as PII, SENSITIVE customer-service users can only see last four digits of columns classified as NATIONAL_ID