Data lake architecture is a storage system designed to hold vast amounts of raw data in its native format until it is needed for analysis. Unlike traditional databases and data warehouses that ...

A data lakehouse addresses these typical limitations of a data lake, as well as data warehouse architecture, by combining the best elements of data warehouses and data lakes to deliver significant ...

Data lake architecture is being utilized across various industries, showcasing its versatility and effectiveness.

Dr. Prakriteswar Santikary, chief data officer at ERT, spoke at Data Architecture Summit 2018 Conference last month about data lake architecture his team developed at their clinical research ...

Data lakehouse architecture combines the best of cloud data lake and warehousing architectures to give teams the most recent data.

It requires new technology to do this. That’s what we call the next generation data lake architecture.” That next generation is based on an ability to separate and scale compute from storage.

Harmonize data lake and data warehouse architecture to drive efficiency and optimization. Apply Gartner’s decision framework to map use cases to data storage options.

The data lakehouse – it’s not a summer retreat for over-worked database administrators (DBAs) or data scientists, it’s a concept that tries to bridge the gap between the data warehouse and ...

In this article, the author shows how to use big data query and processing language U-SQL on Azure Data Lake Analytics platform. U-SQL combines the concepts and constructs both of SQL and C#. It ...

Michigan’s cloud-based system, now in implementation, aims to integrate and refine data from across districts to provide deeper insights into student performance. A small-scale deployment is expected ...