Establish a single data access layer for the use cases requiring the data from multiple sources which may be distributed across on-premise and Cloud platforms.
Description
Establish a single data access layer for the use cases requiring the data from multiple sources which may be distributed across on-premise and Cloud platforms.
Use cases for data virtualization include:
- Data Integration - Combining data from different systems to support analytics, reporting and decision-making
- Data Governance - Enforcing data quality, security, and compliance standards across heterogenous data sources
- Cloud Integration - Connecting on-premises data sources with cloud-based applications and services
Essential components of a data virtualization solution:
1. Data Catalog - centralized repository for storing and managing data
2. Data Quality Management
- Data cleansing - identified and corrects errors, inconsistencies, and duplicates in data
- Data profiling - analyses data to understand its characteristics and quality
3. Integration with existing systems - provides connectors for integrating with various data sources, including databases, cloud applications etc.
4. Security and Governance - Access controls and audit tracking
Eligibility criteria: Tech providers
Expires on December 31, 2024
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