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What is Data Ingestion? Types, Frameworks, Tools, Use Cases

Knowledge Hut

An end-to-end Data Science pipeline starts from business discussion to delivering the product to the customers. One of the key components of this pipeline is Data ingestion. It helps in integrating data from multiple sources such as IoT, SaaS, on-premises, etc., What is Data Ingestion?

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Data Ingestion: 7 Challenges and 4 Best Practices

Monte Carlo

Data ingestion is the process of collecting data from various sources and moving it to your data warehouse or lake for processing and analysis. It is the first step in modern data management workflows. Table of Contents What is Data Ingestion? Decision making would be slower and less accurate.

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Data Pipeline Architecture: Understanding What Works Best for You

Ascend.io

As companies become more data-driven, the scope and complexity of data pipelines inevitably expand. Without a well-planned architecture, these pipelines can quickly become unmanageable, often reaching a point where efficiency and transparency take a backseat, leading to operational chaos. What Is Data Pipeline Architecture?

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An Exploration Of The Expectations, Ecosystem, and Realities Of Real-Time Data Applications

Data Engineering Podcast

Announcements Hello and welcome to the Data Engineering Podcast, the show about modern data management When you’re ready to build your next pipeline, or want to test out the projects you hear about on the show, you’ll need somewhere to deploy it, so check out our friends at Linode. That’s where our friends at Ascend.io

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Handling Bursty Traffic in Real-Time Analytics Applications

Rockset

Though some data sources like event streams were starting to arrive in real time, neither data nor queries were time sensitive. Databases could just buffer, ingest and query data on a regular schedule. Finally, you could always plan ahead for bursty traffic and overprovision your database clusters and pipelines.

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Revolutionizing Real-Time Streaming Processing: 4 Trillion Events Daily at LinkedIn

LinkedIn Engineering

To enable the ingestion and real-time processing of enormous volumes of data, LinkedIn built a custom stream processing ecosystem largely with tools developed in-house (and subsequently open-sourced). In 2010, they introduced Apache Kafka , a pivotal Big Data ingestion backbone for LinkedIn’s real-time infrastructure.

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20+ Data Engineering Projects for Beginners with Source Code

ProjectPro

If you are a newbie in data engineering and are interested in exploring real-world data engineering projects, check out the list of best data engineering project examples below. With the trending advance of IoT in every facet of life, technology has enabled us to handle a large amount of data ingested with high velocity.