Data Lake Analytics

Data Lake an ever-evolving set of technologies which is used to store structured, semi-structured and unstructured data in As-Is state that mean a Data Lake supports all data types and holds big data from many sources in a raw, granular and flexible format.

If business want to observe this data then are many tools in the market to run the requested analytical algorithm processes on the data after proper data cleansing and validations by allowing for real-time actionable insights moving at the speed of your growing business. They can store the processed analytical data back to Data Lake for the dashboards and reporting purposes.

Serverless Computing is the most common, no server management, dynamic and flexible scaling, automated high availability and cost effective feature in Data Lakes behind the success of all the cloud based analytics platforms such as AWS and Azure because it enables self-service provisioning and management of Servers.

1. AWS Serverless Computing platform a set of fully managed services and offers to build and run applications and services without thinking about servers. It eliminates infrastructure management tasks such as server or cluster provisioning, patching, operating system maintenance, and capacity provisioning.
2. Azure Serverless Computing Architecture a set of fully managed service and offers application life cycle and cloud maturity with innovative industry proven solutions, customized to meet the Enterprise Cloud Requirements.