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    Data Pipeline Design Patterns - #1. Data flow patterns

    • Data pipelines can become flakey over time if the data pipeline design foundations are not solid. If you are Then this post is for you. This post will cover the typical data flow design patterns. We will le… See more

    Source & Sink

    Before designing our pipeline, we must understand the inputs and outputs available to us. 1. Source: Systems which provide input(s) to your data pipeline. 2. Sink: Systems w… See more

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    Data Pipeline Patterns

    In this section, we will go over extraction, behavior, & structural patterns. One can combine these patterns based on your use case. For example, you might have a data pipeline tha… See more

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    Conclusion

    This article gives you a good idea of the typical design patterns for organizing data flows through your pipeline. To recap, we saw. 1. Types of Sources & Sinks 2. Data flow desig… See more

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    Further Reading

    Data pipeline testing
    What are facts and dimensions?
    What is an SCD2 table?
    How to build idempotent pipelines? See more

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    References

    Ecotrust canada TOC generator
    dbt docs
    Databricks docs See more

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