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Presentation Title: Delta Table Optimization - Improving Queries using Delta Partitioning and Liquid Clustering

Description:

Data volumes are skyrocketing, and with every new project, the pressure is on for data engineers to deliver snappy queries over ever-growing datasets. In this session, we’ll dive deep into how Delta Lake’s partitioning and Liquid Clustering capabilities can transform query performance in Microsoft Fabric. We’ll put these optimizations to the test against a massive dataset—millions (or even billions!) of rows—to demonstrate real-world impacts on speed and efficiency.

You’ll explore the nuts and bolts of Delta partitioning to ensure your data is stored in the most optimal way, reducing query overhead and slashing runtimes. Then we’ll crank it up a notch with Liquid Clustering, an advanced feature that automatically reorganizes your data for blazing-fast analytics.

Finally, we’ll show how to integrate these Delta optimizations into your Microsoft Fabric Lakehouse, so you can power dashboards, reports, or machine learning pipelines with near real-time insights—without those dreaded performance bottlenecks.

By the end of this session, you will:
🔹 Understand how and why Delta partitioning supercharges query performance
🔹 Harness Liquid Clustering in Delta Lake to keep your data lean, mean, and query-ready
🔹 Integrate partitioned and clustered Delta tables seamlessly with Microsoft Fabric for next-level analytics

Brace yourself: this session may contain dangerously optimized partition strategies and an overdose of high-speed query demos! If you’re a data engineer looking for hands-on techniques to crush query latencies and boost productivity in Microsoft Fabric, this is your must-attend deep dive. Get ready to leave your old, slow queries in the dust.

Apache Spark
Big Data
Data Analytics
Business Intelligence & Data Warehousing
Python

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