Remove Data Pipeline Remove Engineering Remove ETL Tools
article thumbnail

Data Pipeline vs. ETL: Which Delivers More Value?

Ascend.io

In the modern world of data engineering, two concepts often find themselves in a semantic tug-of-war: data pipeline and ETL. Fast forward to the present day, and we now have data pipelines. However, they are not just an upgraded version of ETL. Yet, the technical problem is the same.

article thumbnail

Data Engineer vs Data Analyst: Key Differences and Similarities

Knowledge Hut

With companies increasingly relying on data-driven insights to make informed decisions, there has never been a greater need for skilled specialists who can manage and evaluate vast amounts of data. The roles of data analyst and data engineer have emerged as two of the most in-demand professions in today's job market.

Insiders

Sign Up for our Newsletter

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

article thumbnail

What is a Data Pipeline?

Grouparoo

As a result, data has to be moved between the source and destination systems and this is usually done with the aid of data pipelines. What is a Data Pipeline? A data pipeline is a set of processes that enable the movement and transformation of data from different sources to destinations.

article thumbnail

Why Modernizing the First Mile of the Data Pipeline Can Accelerate all Analytics

Cloudera

Whether it is consuming log files, sensor metrics, and other unstructured data, most enterprises manage and deliver data to the data lake and leverage various applications like ETL tools, search engines, and databases for analysis. Let’s transform the first mile of the data pipeline.

article thumbnail

An Introduction To Data And Analytics Engineering For Non-Programmers

Data Engineering Podcast

In this episode Brian McMillan shares his work on the book "Building Data Products" and how he is working to educate business users and data professionals about the combination of technical, economical, and business considerations that need to be blended for these projects to succeed.

article thumbnail

Data Engineering Weekly #153

Data Engineering Weekly

Lorin Hochstein: “Human error” means they don’t understand how the system worked The post is not directly related to Data Engineering but system operations in general. I included this post because I often see high-pitched LinkedIn posts stating it is the human fault, especially around data quality issues. .”

article thumbnail

Data Pipeline with Airflow and AWS Tools (S3, Lambda & Glue)

Towards Data Science

Today’s post follows the same philosophy: fitting local and cloud pieces together to build a data pipeline. And, when it comes to data engineering solutions, it’s no different: They have databases, ETL tools, streaming platforms, and so on — a set of tools that makes our life easier (as long as you pay for them).