Enterprises sit on vast reserves of diverse, potentially invaluable data such as databases, social media, logs, and sensor data locked in data silos. The Data Lake is schema-less and stores data of any type and format. Not only storing, but offering the ability to integrate data from disparate sources and ingest high-velocity, multi-structured and massive datasets. This key feature empowers enterprises to perform exploratory and advanced data analysis on all the data and quickly gain actionable insights.
Before the Data Lake is utilized to its hilt to perform data analysis, there should be mechanisms implemented to seamlessly connect the Data Lake to various external data sources and acquire data from them. The Intake Tier in the Data Lake architecture implements the functionalities needed to address this. In the following subsection, let us study the Intake Tier in detail.
Let us start by understanding the data flow from the External Data Sources to the Intake...
