Data Engineering Podcast

FEBRUARY 18, 2024

Announcements Hello and welcome to the Data Engineering Podcast, the show about modern data management Dagster offers a new approach to building and running data platforms and data pipelines. Data lakes are notoriously complex. Data lakes are notoriously complex. Your first 30 days are free!

Data Lake 262

Data Lake High Quality Data Data Warehouse Google Cloud 262

Data Engineering Podcast

MAY 26, 2024

Announcements Hello and welcome to the Data Engineering Podcast, the show about modern data management Data lakes are notoriously complex. Announcements Hello and welcome to the Data Engineering Podcast, the show about modern data management Data lakes are notoriously complex.

Systems 130

Systems Data Lake High Quality Data Google Cloud 130

Monte Carlo

FEBRUARY 20, 2024

Let’s explore what to consider when thinking about data ingestion tools and explore the leading tools in the field. The self-hosted option allows for scalability based on the underlying infrastructure, while the cloud version manages scalability for you. Google Cloud Dataflow Image courtesy of Google Cloud.

Data Ingestion 52

Data Ingestion Google Cloud Kafka AWS 52

ProjectPro

FEBRUARY 21, 2023

Vendor-Specific Data Engineering Certifications The vendor-specific data engineer certifications help you enhance your knowledge and skills relevant to specific vendors, such as Azure, Google Cloud Platform, AWS, and other cloud service vendors. The rest of the exam details are the same as the DP-900 exam.

Certification 52

Certification Data Engineering Data Engineer Engineering 52

Monte Carlo

MAY 17, 2023

Data Warehouse (Or Lakehouse) Migration 34. Integrate Data Stacks Post Merger 35. Know When To Fix Vs. Refactor Data Pipelines Improve DataOps Processes 37. Analyze Data Incident Impact and Triage 39. Transition To A Data Mesh (Or Other Data Team Structure) 40. Prioritize Data Assets And Efforts 41.

Data 52

Data Data Pipeline Data Engineering Data Engineer 52

Monte Carlo

MAY 17, 2023

Data warehouse (or Lakehouse) migration 34. Integrate Data Stacks Post Merger 35. Know When To Fix Vs. Refactor Data Pipelines Improve DataOps Processes 37. Analyze Data Incident Impact and Triage 39. Transition To A Data Mesh (Or Other Data Team Structure) 40. Prioritize Data Assets And Efforts 41.

Data Pipeline 52

Data Pipeline Data Data Engineering Data Engineer 52