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.

ETL Tools 52

ETL Tools IT Data Pipeline Data Warehouse 52

Ascend.io

MAY 31, 2023

Data Ingestion Data ingestion is the first step of both ETL and data pipelines. In the ETL world, this is called data extraction, reflecting the initial effort to pull data out of source systems. The data sources themselves are not built to perform analytics.

Data Pipeline 52

Data Pipeline ETL Tools Pipeline-centric Data Warehouse 52

Ascend.io

OCTOBER 28, 2024

Advanced Data Transformation Techniques For data engineers ready to push the boundaries, advanced data transformation techniques offer the tools to tackle complex data challenges and drive innovation.

Raw Data 52

Raw Data Datasets Aggregated Data Data Pipeline 52

Knowledge Hut

NOVEMBER 17, 2023

cloud Technical Skills for Azure Data Engineers Here I have listed the skills required for an Azure data engineer: 1. Programming and Scripting Languages Proficiency in languages like Python for data manipulation and SQL for database querying, enabling efficient data processing and analysis.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Lake 52

Knowledge Hut

MARCH 28, 2024

Salary (Average) $135,094 per year (Source: Talent.com) Top Companies Hiring Deloitte, IBM, Capgemini Certifications Microsoft Certified: Azure Solutions Architect Expert Job Role 3: Azure Big Data Engineer The focus of Azure Big Data Engineers is developing and implementing big data solutions with the use of the Microsoft Azure platform.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Warehouse 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

Edureka

JULY 3, 2024

You can extract data efficiently and once gathered, you can transform this data using built-in or custom transformations, and then load it into your desired destination. And let’s not forget the cherry on top – the ability to reuse code across different Data Factory instances. Is Azure Data Factory an ETL tool?

Pipeline-centric 52

Pipeline-centric Data Lake Database-centric Data Pipeline 52