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Build Data Pipelines: Comprehensive Step-by-Step Guide

Pickl AI

Definition and Explanation of Data Pipelines A data pipeline is a series of interconnected steps that ingest raw data from various sources, process it through cleaning, transformation, and integration stages, and ultimately deliver refined data to end users or downstream systems.

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7 Best Machine Learning Workflow and Pipeline Orchestration Tools 2024

DagsHub

Flexibility: Its use cases are wider than just machine learning; for example, we can use it to set up ETL pipelines. Also, while it is not a streaming solution, we can still use it for such a purpose if combined with systems such as Apache Kafka. Miscellaneous Workflows are created as directed acyclic graphs (DAGs).

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How to Manage Unstructured Data in AI and Machine Learning Projects

DagsHub

For instance, if you are working with several high-definition videos, storing them would take a lot of storage space, which could be costly. Apache Kafka Apache Kafka is a distributed event streaming platform for real-time data pipelines and stream processing. Unstructured.io

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The Evolution of Customer Data Modeling: From Static Profiles to Dynamic Customer 360

phData

Technologies like Apache Kafka, often used in modern CDPs, use log-based approaches to stream customer events between systems in real-time. In traditional ETL (Extract, Transform, Load) processes in CDPs, staging areas were often temporary holding pens for data. But the power of logs doesn’t stop there.