Following are key data lake concepts that one needs to understand to completely understand the data lake architecture.
Open source data lake architecture.
To support our customers as they build data lakes aws offers the data lake solution which is an automated reference implementation that deploys a highly available cost effective data lake architecture on the aws cloud along with a user friendly console for searching and requesting datasets.
All types of structured semi structured and unstructured data.
A data lake architecture.
Kylo is an open source enterprise ready data lake management software platform for self service data ingest and data preparation with integrated metadata management governance security and best practices inspired by think big s 150 big data implementation projects.
Data lake architecture makes use of metadata both business and technical in order to determine data characteristics and arrive at data supported decisions.
An enterprise data lake edl is simply a data lake for enterprise wide information storage and sharing.
All content will be ingested into the data lake or staging repository based on cloudera and then.
A data lake architecture incorporating enterprise search and analytics techniques can help companies unlock actionable insights from the vast structured and unstructured data stored in their lakes.
Data ingestion allows connectors to get data from a different data sources and load into the data lake.