Smart Data Lake platforms providing semantic layers are automating data access and data management for accelerated insight. These platforms, based on knowledge graphs, allow organizations on-demand access to all relevant data, internal or external, regardless of the source format or type (i.e. structured, unstructured or semi-structured). All resulting in faster answers to questions impacting an enterprise. Now IT organizations can easily deliver harmonized diverse data sets with full richness allowing various stakeholders to conduct interactive high resolution analytics on the multi-layered rich data. Stakeholders can also use these Smart Data Lakes with semantic layers for on-demand discovery of right data and data sets to be used with business intelligence, machine learning or advanced analytics systems without any IT set up or preparation. The result - better insights, improved time to market, and faster and timely decision making.
Organizations must provide the right data to the right resources at the right time. Business needs change. Timely data leads to timely insights. With growth of variety and volume of data, manual coding and manual data preparation are no longer viable. Traditional data warehouses and conventional “Big Data” technologies are costly to set up and fall short when business needs or data sources change. New proven smart data lake technologies with semantic layers provide a smarter approach to handling and managing data.
What Has Changed?
- Fast processing - the processing overhead of knowledge graphs and semantic layers are no longer an issue. Now users can have rich data analytics at scale.
- Cheap storage - data lakes provide easy and cheap facilities to store original data. Smart Data Lakes make data stored in these cheap storage systems understandable and usable.
- Cloud - cloud systems provide ubiquitous access with on-demand provisioning of servers for Smart Data Lake analysis and making large scale analysis affordable and scalable.
- Open semantic data standards and industry standards allow for common business understanding of corporate entities, rules and processes.
- Managing Director, Leading Investment Bank
5 Key Questions to Identify the Need for Smart Data Lakes with Semantic Layers
- Do you have real-time business understanding of what data lies in which system?
- Can you bring together data from diverse systems without manual coding?
- Is your data managed and governed based on company and industry standards?
- Can users discover, analyze and get data at Big Data scale when they need it?
- Do you have the foundation for advanced analytics and machine learning?
What Do You Need in a Semantic Data Layer to Provide On-Demand Data Access?
- Single source of common business understanding of all enterprise data – structured & unstructured.
- Automated data management using ETL or ELT code generation from common business models to move and manage data from any source system(s) to any target system(s) to serve.
- Ability to discover, analyze and push data to machine learning, advanced analytics and third party systems
- High resolution analytics at Big Data scale
- Enterprise grade security and governance
To learn more about Smart Data Lakes, download our whitepaper "Anzo Smart Data Lake® Whitepaper".