Remove 2024 Remove Azure Remove Data Pipeline
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11 Open-Source Data Engineering Tools Every Pro Should Use

ODSC - Open Data Science

Apache Kafka For data engineers dealing with real-time data, Apache Kafka is a game-changer. This open-source streaming platform enables the handling of high-throughput data feeds, ensuring that data pipelines are efficient, reliable, and capable of handling massive volumes of data in real-time.

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How to Shift from Data Science to Data Engineering

ODSC - Open Data Science

Data engineers will also work with data scientists to design and implement data pipelines; ensuring steady flows and minimal issues for data teams. They’ll also work with software engineers to ensure that the data infrastructure is scalable and reliable. Learn more about the cloud.

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How to Trigger a Slack Notification When a Pipeline Fails in Fivetran

phData

This article was co-written by Mayank Singh & Ayush Kumar Singh Your organization’s data pipelines will inevitably run into issues, ranging from simple permission errors to significant network or infrastructure incidents. Failed Webhooks If webhooks are configured and the webhook event fails, a notification will be sent out.

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ODSC West 2023 Recap in Pictures

ODSC - Open Data Science

While we may be done with events for 2023, 2024 is looking to be packed full of conferences, meetups, and virtual events. On the horizon is ODSC East 2024, which is shaping up to be just as packed with content as ODSC West was, but with its own spin on things. What’s next? Right now, tickets are 75% off for a limited time!

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Using Matillion Data Productivity Cloud to call APIs

phData

Matillion’s Data Productivity Cloud is a versatile platform designed to increase the productivity of data teams. It provides a unified platform for creating and managing data pipelines that are effective for both coders and non-coders. Check out the API documentation for our sample.

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How to Setup a Project in Snowpark Using a Python IDE

phData

Developers can seamlessly build data pipelines, ML models, and data applications with User-Defined Functions and Stored Procedures. If your data pipeline requirements are quite straightforward—i.e., You have different developers working on building data pipelines/UDFs/stored procedures in the same environment.

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AIOps vs. MLOps: Harnessing big data for “smarter” ITOPs

IBM Journey to AI blog

Wearable devices (such as fitness trackers, smart watches and smart rings) alone generated roughly 28 petabytes (28 billion megabytes) of data daily in 2020. And in 2024, global daily data generation surpassed 402 million terabytes (or 402 quintillion bytes). Massive, in fact.

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