optimization▌

Identify cost savings across Azure subscriptions through resource analysis, utilization metrics, and actionable optimization recommendations. \n \n Discovers orphaned resources (unattached disks, unused NICs, idle gateways) and over-provisioned services using Azure Quick Review \n Queries actual costs from Azure Cost Management API and utilization data from Azure Monitor to support rightsizing recommendations \n Generates prioritized optimization reports with estimated savings, implementation co

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Apache Spark job optimization through partitioning, memory tuning, shuffle reduction, and join strategies. \n \n Covers partitioning strategies, broadcast joins, bucketed joins, and skew handling with salting techniques to minimize shuffle overhead \n Includes caching and persistence patterns with storage level selection, checkpointing for complex lineages, and memory configuration breakdown \n Provides data format optimization for Parquet and Delta Lake, column pruning, predicate pushdown, and