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End-to-End Data Engineering System on Real Data with Kafka, Spark, Airflow, Postgres, and Docker

Towards Data Science

This article is part of a project that’s split into two main phases. This first part project is ideal for beginners in data engineering, as well as for data scientists and machine learning engineers looking to deepen their knowledge of the entire data handling process. Overview of the data pipeline. Image by the author.

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15+ AWS Projects Ideas for Beginners to Practice in 2023

ProjectPro

With over 1 million active enterprise customers, 8K AWS partner network members,1900+ third-party software products, and over 70 million hours spent on the Amazon Marketplace monthly by its customers - AWS is a name to reckon with in the cloud computing industry. Rapid Document Conversion 2. Table of Contents What is AWS?

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Securely Scaling Big Data Access Controls At Pinterest

Pinterest Engineering

As a core part of our architecture, we created a dedicated service (the Credential Vending Service, or CVS) to securely perform AssumeRole calls which could map users to permissions and Managed Policies. list, read, write) on different S3 endpoints. User 1 is a member of two FGAC LDAP groups: i.

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Modern Data Engineering

Towards Data Science

Often it is a data warehouse solution (DWH) in the central part of our infrastructure. I previously wrote about it in one of my stories on Apache Iceberg table format [2]. Typical Airflow architecture includes a schduler based on metadata, executors, workers and tasks. ML model training using Airflow.