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Data Engineering Zoomcamp – Data Ingestion (Week 2)

Hepta Analytics

DE Zoomcamp 2.2.1 – Introduction to Workflow Orchestration Following last weeks blog , we move to data ingestion. We already had a script that downloaded a csv file, processed the data and pushed the data to postgres database. This week, we got to think about our data ingestion design.

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Azure Data Engineer Job Description [Roles and Responsibilities]

Knowledge Hut

Microsoft Azure is a cloud computing platform that gives businesses fantastic services. This demonstrates how in-demand Microsoft Certified Data Engineers are becoming. To start a successful career in cloud computing, you must have a solid conceptual foundation.

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Top 10 Azure Data Engineer Job Opportunities in 2024 [Career Options]

Knowledge Hut

Role Level: Intermediate Responsibilities Design and develop big data solutions using Azure services like Azure HDInsight, Azure Databricks, and Azure Data Lake Storage. Implement data ingestion, processing, and analysis pipelines for large-scale data sets.

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Azure Data Engineer (DP-203) Certification Cost in 2023

Knowledge Hut

Why Should You Get an Azure Data Engineer Certification? Becoming an Azure data engineer allows you to seamlessly blend the roles of a data analyst and a data scientist. One of the pivotal responsibilities is managing data workflows and pipelines, a core aspect of a data engineer's role.

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Data Pipeline Architecture Explained: 6 Diagrams and Best Practices

Monte Carlo

Why is data pipeline architecture important? Some organizations choose to still leverage an ETL pattern in the cloud, particularly for production pipelines where data contracts can help reduce data downtime. Singer – An open source tool for moving data from a source to a destination.

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From Patchwork to Platform: The Rise of the Post-Modern Data Stack

Ascend.io

In the data world, this disruption manifested in the form of cloud computing with technologies such as Redshift, Snowflake, and Spark. In our case, data ingestion, transformation, orchestration, reverse ETL, and observability. This is the modern data stack as we know it today. Sounds familiar?