Data Engineering Guide

ETL processing has been around since the 1970s but 40 years later many organizations continue to suffer from the constraints of traditional batch processing

ETL stands for 'extract, transform, load', the three processes that move data from one database, multiple databases, or other sources to a unified repository.

An ETL pipeline is the set of processes used to move data from a source or multiple sources into a database such as a data warehouse. Learn more.

Machine learning is an application of artificial intelligence (AI) that enables systems to learn automatically and improve through experience without the assistance of explicit programming.

JSON is an open-standard data format or interchange for semi-structured data. It is text-based and can be read by humans and machines.

This guide article explains the difference between structured and semi-structured data and why your data platform must support both for your organization to be fully data-driven.

A CI/CD pipeline is a software development or engineering process that combines automated code building and testing with deployment. Learn more.

In this guide we are talking about what Is IoT, how does it work, and what is the business value of IoT Data. Learn more.

Master Data Management (MDM), which goes hand in hand with data governance, has moved to the forefront of data-driven organizations.