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Data science teams cannot create a model and “throw it over the fence” to another team. Everyone needs to work together to achieve value, from businessintelligence experts, data scientists, and process modelers to machine learning engineers, software engineers, business analysts, and end users.
Data Quality Check: As the data flows through the integration step, ETL pipelines can then help improve the quality of data by standardizing, cleaning, and validating it. This ensures that the data which will be used for ML is accurate, reliable, and consistent. 4 How to create scalable and efficient ETL data pipelines.
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