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Consulting Case Study: Job Market Analysis

WeCloudData

By leveraging data engineering techniques combined with a cloud toolchain, WeCloudData helped a client achieve a continuous flow of current job market data with analytical capabilities and dashboards to drive the business forward and stay competitive.

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Consulting Case Study: Job Market Analysis

WeCloudData

By leveraging data engineering techniques combined with a cloud toolchain, WeCloudData helped a client achieve a continuous flow of current job market data with analytical capabilities and dashboards to drive the business forward and stay competitive.

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Machine Learning with Python, Jupyter, KSQL and TensorFlow

Confluent

It allows real-time data ingestion, processing, model deployment and monitoring in a reliable and scalable way. This blog post focuses on how the Kafka ecosystem can help solve the impedance mismatch between data scientists, data engineers and production engineers.

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Data Pipeline- Definition, Architecture, Examples, and Use Cases

ProjectPro

Consequently, data engineers implement checkpoints so that no event is missed or processed twice. It not only consumes more memory but also slackens data transfer. Modern cloud-based data pipelines are agile and elastic to automatically scale compute and storage resources. ADF does not store any data on its own.

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Most important Data Engineering Concepts and Tools for Data Scientists

DareData

Our goal is to help data scientists better manage their models deployments or work more effectively with their data engineering counterparts, ensuring their models are deployed and maintained in a robust and reliable way. AWS Glue: A fully managed data orchestrator service offered by Amazon Web Services (AWS).

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20+ Data Engineering Projects for Beginners with Source Code

ProjectPro

Data Engineering Project for Beginners If you are a newbie in data engineering and are interested in exploring real-world data engineering projects, check out the list of data engineering project examples below. This big data project discusses IoT architecture with a sample use case.

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Data Warehousing Guide: Fundamentals & Key Concepts

Monte Carlo

Since the inception of the cloud, there has been a massive push to store any and all data. On the surface, the promise of scaling storage and processing is readily available for databases hosted on AWS RDS, GCP cloud SQL and Azure to handle these new workloads. Cloud data warehouses solve these problems.