IBM Journey to AI blog

SEPTEMBER 2, 2024

Historically, data engineers have often prioritized building data pipelines over comprehensive monitoring and alerting. Delivering projects on time and within budget often took precedence over long-term data health. Often, data teams must follow a manual process to help ensure data accuracy.

Data Observability 52

Data Observability Data Pipeline Data Engineering Data Engineering 52

ODSC - Open Data Science

DECEMBER 19, 2023

billion by 2026. Data Engineer Data engineers are responsible for the end-to-end process of collecting, storing, and processing data. They use their knowledge of data warehousing, data lakes, and big data technologies to build and maintain data pipelines. billion in 2021 to $331.2

Data Scientist 96

Data Scientist Machine Learning Machine Learning Computer Science 96

AWS Machine Learning Blog

JUNE 13, 2025

Training pipeline management The success of the training process heavily relied on maintaining high-quality data pipelines. The following screenshot shows an example of the memory consumption prediction tool interface ( original image ).

AWS 106

AWS Clustering Machine Learning Machine Learning 106

Pickl AI

NOVEMBER 4, 2024

Effective data governance enhances quality and security throughout the data lifecycle. What is Data Engineering? Data Engineering is designing, constructing, and managing systems that enable data collection, storage, and analysis. They are crucial in ensuring data is readily available for analysis and reporting.

Data Engineering 52

Data Engineering Data Engineering Data Engineering Data Engineer 52

Flipboard

JUNE 16, 2025

Must-Have Skills for Data Engineers: Cloud Platforms : Expertise in AWS, Azure, and Google Cloud Platform (GCP) is vital for managing and deploying cloud-based data infrastructure. Database Management : It is crucial to have knowledge of both relational (e.g., MySQL, PostgreSQL) and non-relational (e.g., MongoDB, Cassandra) databases.

Python 50

Python AWS Machine Learning Machine Learning 50