Data Access Layer (DAL)
DAL is a cutting-edge data product that delivers a fast, scalable, and highly customizable data lakehouse, driven by Trino, the leading SQL analytics engine. DAL offers a high-performance data architecture designed for rapid data processing and analytics, effectively managing complex queries over large datasets. It provides a scalable and cost-effective lakehouse solution, complete with robust security and governance features, ensuring seamless operation for your business, engineering, and analytics teams.
Features
- All data sources can be accessed through a single layer DAL. It provides centralized access control for all the sources.
Simplified Data Access
- DAL connects to various data sources, whether on-premises, in the cloud, or in a hybrid environment, offering flexibility.
Hybrid and Multi-Cloud Support
- DAL offers real-time data access, ensuring up-to-date information from various sources without delays.
Real-time Data Access
- Supports querying multiple data sources via SQL, eliminating silos and allowing seamless data integration.
Data Virtualization
- Enables users to explore data independently without heavy reliance on IT teams.
Self-Service Analytics
- DAL queries petabytes of data across Data Lakes and relational sources.
Scalability
Benefits
Centralized Data Management
DAL simplifies access by consolidating multiple data sources into a single layer, providing centralized access control and streamlining data governance.
Elimination of Data Silos
Supports querying heterogeneous data sources through a single SQL query, integrating data seamlessly for better insights.
Flexible Infrastructure Support
Connects to data sources across on-premises, cloud, or hybrid environments, aligning with modern data architectures.
Empowered Self-Service Analytics
Enables users to explore and analyze data without constant IT support, boosting productivity.
Real-Time Data Processing
Provides real-time access to data from multiple sources for improved decision-making.
Scalable and Cost-Effective
Handles large-scale data efficiently while maintaining cost-effectiveness.
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