Well-optimized ETL processes provide high-quality data flowing through your pipelines.
However, studies suggest that more than 80% of enterprise data is unstructured, often leading to inaccuracies in analytics platforms.
This can create a misleading picture for businesses and affect overall decision-making.
To address these challenges, implementing best practices can help data professionals refine their data precisely.
In this blog post, we will explore some proven key ETL optimization strategies for handling massive datasets in large-scale pipelines.
Let us start:
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