Ascend.io

DECEMBER 19, 2023

We’ll talk about when and why ETL becomes essential in your Snowflake journey and walk you through the process of choosing the right ETL tool. Our focus is to make your decision-making process smoother, helping you understand how to best integrate ETL into your data strategy. But first, a disclaimer.

ETL Tools 52

ETL Tools IT Data Pipeline Data Warehouse 52

Knowledge Hut

NOVEMBER 17, 2023

The job of an Azure Data Engineer is really needed in the world of handling and studying data. As Azure Data Engineers, they'll be responsible for creating and looking after solutions that use data to help the company. Azure Data Factory stands at the forefront, orchestrating data workflows.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Lake 52

Knowledge Hut

MARCH 28, 2024

Job Role 1: Azure Data Engineer Azure Data Engineers develop, deploy, and manage data solutions with Microsoft Azure data services. They use many data storage, computation, and analytics technologies to develop scalable and robust data pipelines.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Warehouse 52

Ascend.io

MAY 31, 2023

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.

Data Pipeline 52

Data Pipeline ETL Tools Pipeline-centric Data Warehouse 52

Meltano

OCTOBER 5, 2022

A data engineer must figure out how the data will be structured, test data pipelines, and keep an eye on the entire data management process. However, to do their jobs well, data engineers require proper tools and solutions to facilitate the extraction of data from multiple sources.

Data Engineering 52

Data Engineering Data Engineer Engineering Raw Data 52

Meltano

OCTOBER 5, 2022

In the same way, a DataOps engineer designs the data assembly line that enables data scientists to derive insights from data analytics faster and with fewer errors. DataOps engineers improve the speed and quality of the data development process by applying DevOps principles to data workflow, known as DataOps.

Engineering 52

Engineering Raw Data Data Pipeline ETL Tools 52