Knowledge Hut

DECEMBER 26, 2023

Data Engineering is typically a software engineering role that focuses deeply on data – namely, data workflows, data pipelines, and the ETL (Extract, Transform, Load) process. A simple usage of Business Intelligence (BI) would be enough to analyze such datasets. What is the need for Data Science?

Data Engineering 98

Data Engineering Data Engineer Engineering Pipeline-centric 98

Knowledge Hut

JUNE 20, 2023

In addition, they are responsible for developing pipelines that turn raw data into formats that data consumers can use easily. He researches, develops, and implements artificial intelligence (AI) systems to automate predictive models. Apache Spark, Microsoft Azure, Amazon Web services, etc.

Machine Learning 52

Machine Learning Data Engineering Data Engineer Engineering 52

Knowledge Hut

FEBRUARY 27, 2023

Data engineering builds data pipelines for core professionals like data scientists, consumers, and data-centric applications. A data engineer can be a generalist, pipeline-centric, or database-centric. They manage data considering trends and discrepancies that impact business goals.

Data Engineering 52

Data Engineering Data Engineer Database-centric Pipeline-centric 52

phData: Data Engineering

JULY 18, 2023

This typically results in long-running ETL pipelines that cause decisions to be made on stale or old data. Business-Focused Operation Model: Teams can shed countless hours of managing long-running and complex ETL pipelines that do not scale. This enables an automated continuous integration/continuous deployment system (CI/CD).

Data Warehouse 52

Data Warehouse Pipeline-centric Government Data 52