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

Databand.ai

AUGUST 30, 2023

DataOps is a collaborative approach to data management that combines the agility of DevOps with the power of data analytics. It aims to streamline data ingestion, processing, and analytics by automating and integrating various data workflows.

Architecture 52

Architecture Data Ingestion Data Governance Data Cleanse 52

Databand.ai

AUGUST 30, 2023

By using DataOps tools, organizations can break down silos, reduce time-to-insight, and improve the overall quality of their data analytics processes. DataOps tools can be categorized into several types, including data integration tools, data quality tools, data catalog tools, data orchestration tools, and data monitoring tools.

Data Cleanse 52

Data Cleanse Data Pipeline Data Ingestion Data Validation 52

Databand.ai

AUGUST 30, 2023

Integrating these principles with data operation-specific requirements creates a more agile atmosphere that supports faster development cycles while maintaining high quality standards. This demands the implementation of advanced data integration techniques, such as real-time streaming ingestion, batch processing, and API-based access.

Data Governance 40

Data Governance Data Cleanse Government Data Pipeline 40

Knowledge Hut

MARCH 28, 2024

Role Level Advanced Responsibilities Design and architect data solutions on Azure, considering factors like scalability, reliability, security, and performance. Develop data models, data governance policies, and data integration strategies. Familiarity with ETL tools and techniques for data integration.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Warehouse 52

Monte Carlo

MAY 25, 2023

Automated data orchestration removes data bottlenecks by eliminating the need for manual data preparation, enabling analysts to both extract and activate data in real-time. Improved data governance. So, who’s responsible for data integration? Automating data workflows.

Data Pipeline 52

Data Pipeline Data Workflow Data Data Governance 52

Monte Carlo

MAY 14, 2024

Delta Lake : Released by Databricks in 2019, Delta Lake was created to bring reliability and robustness to data lakes, incorporating ACID (Atomicity, Consistency, Isolation, Durability) transactions into Apache Spark to maintain data integrity across complex transformations and updates.

Data Lake 52

Data Lake Metadata Hadoop Data Governance 52