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Data Architect: Role Description, Skills, Certifications and When to Hire

AltexSoft

It serves as a foundation for the entire data management strategy and consists of multiple components including data pipelines; , on-premises and cloud storage facilities – data lakes , data warehouses , data hubs ;, data streaming and Big Data analytics solutions ( Hadoop , Spark , Kafka , etc.);

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Which Team Should Own Data Quality?

Towards Data Science

Specialists or generalists? We examine which team structures are the best suited for efficiently improving data quality. Sure, data quality is everyones’ problem. For one, data engineers are often in short supply and so focused on systems and pipelines that they don’t always have as deep domain knowledge of the data.

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Top 20+ Big Data Certifications and Courses in 2023

Knowledge Hut

Problem-Solving : Strong problem-solving abilities are crucial for solving complex data challenges and efficient data processing. Data Security and Privacy : Considering the sensitivity of data handled in Big Data projects , it is crucial to have awareness of data security and privacy concerns.

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97 things every data engineer should know

Grouparoo

This provided a nice overview of the breadth of topics that are relevant to data engineering including data warehouses/lakes, pipelines, metadata, security, compliance, quality, and working with other teams. 69 The End of ETL as We Know It Use events from the product to notify data systems of changes.