Guided Project: Data Pipeline in Spring Boot using Kafka

David Landup
Arpendu Kumar Garai

The concept of a data pipeline is not new, and many firms have utilized them for years (sometimes without their knowledge), albeit in different configurations than the ones we see today. Data pipelines are crucial for firms to have, as the expansion of company data continues to grow exponentially year after year.

Data pipelines are vital in the fields of data analytics and business analysis, but they also offer numerous advantages and applications beyond business intelligence. Today, we'll discuss the benefits of data pipelines, what a data pipeline entails, and provide a high-level technical overview of its essential components.

A data pipeline, simply put, is a set of actions that transfer unprocessed, structured, or unstructured data from a source to a destination. There can be various types of sources, but in this context, a source can be a transactional database, whereas the typical destination can be a data lake or a data warehouse. The final location is where the data is examined for business insights. In this entire journey from source to destination, various types of transformation logic are applied to the extracted data at different levels to make it ready for quick analysis and presentation or visualization in the User Interface.

Start course to continue
Lessson 12/14
You must first start the course before tracking progress.
Mark completed

© 2013-2024 Stack Abuse. All rights reserved.