Remove Aggregated Data Remove Cloud Storage Remove Data Ingestion
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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. DigDag: An open-source orchestrator for data engineering workflows.

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Consulting Case Study: Job Market Analysis

WeCloudData

Furthermore, one cannot combine and aggregate data from publicly available job boards into custom graphs or dashboards. The client needed to build its own internal data pipeline with enough flexibility to meet the business requirements for a job market analysis platform & dashboard.

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Consulting Case Study: Job Market Analysis

WeCloudData

Furthermore, one cannot combine and aggregate data from publicly available job boards into custom graphs or dashboards. The client needed to build its own internal data pipeline with enough flexibility to meet the business requirements for a job market analysis platform & dashboard.

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A Breakthrough Architecture for Real-Time Analytics- An Overview of Compute-Compute Separation in Rockset

Rockset

Developers can spin up or down virtual instances based on the performance requirements of their streaming ingest or query workloads. In addition, Rockset provides fast data access through the use of more performant hot storage, while cloud storage is used for durability.

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Data Warehousing Guide: Fundamentals & Key Concepts

Monte Carlo

Key Functions of a Data Warehouse Any data warehouse should be able to load data, transform data, and secure data. Data Loading This is one of the key functions of any data warehouse. Data can be loaded in batches or can be streamed in near real-time. They need to be transformed.

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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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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.