A collection of technical blogs, including code samples and notebooks
Organizations recognize data as a strategic asset for initiatives like increasing revenue, enhancing customer experience, operating efficiently, or improving products and services. However, managing this data has become complex due to the explosion of data volumes and types, with 80% being unstructured or semi-structured. As data collection grows, 73% of data remains unused for analytics or decision-making. To reduce this percentage, data engineers build pipelines to deliver data efficiently, facing several challenges:
The Databricks Lakehouse Platform provides an end-to-end data engineering solution for ingesting, transforming, processing, scheduling, and delivering data. It automates building and maintaining pipelines and running ETL workloads directly on a data lake, allowing data engineers to focus on quality and reliability to drive valuable insights.
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