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

ProjectPro

A pipeline may include filtering, normalizing, and data consolidation to provide desired data. It can also consist of simple or advanced processes like ETL (Extract, Transform and Load) or handle training datasets in machine learning applications. In most cases, data is synchronized in real-time at scheduled intervals.

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Data Warehousing Guide: Fundamentals & Key Concepts

Monte Carlo

A company’s production data, third-party ads data, click stream data, CRM data, and other data are hosted on various systems. An ETL tool or API-based batch processing/streaming is used to pump all of this data into a data warehouse. The following diagram explains how integrations work.

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Data Integration: Approaches, Techniques, Tools, and Best Practices for Implementation

AltexSoft

With it, data is retrieved from its sources, migrated to a staging data repository where it undergoes cleaning and conversion to be further loaded into a target source (commonly data warehouses or data marts ). A newer way to integrate data into a centralized location is ELT. Data consolidation.