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To design an extensible analytics data model and pipeline, start by defining your data sources, identifying key metrics, and understanding the analytics requirements. Create a flexible data model that can accommodate future data sources and evolving business needs. Develop a scalable pipeline using tools like Apache Spark or Apache Flink to process and analyze data efficiently. Implement data governance practices to ensure data quality and consistency. Regularly review and iterate on your data model and pipeline to adapt to changing requirements.
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