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Welcome to BIPro #103, your weekly digest of the top breakthroughs, practical insights, and real-world applications driving business intelligence forward. This edition covers everything from real-time AI integrations to SQL tuning tips, with direct links to help you dive deeper.

Key Highlights:

🧠 Stay sharp, stay connected. BIPro brings you the trends that matter and the tools to act on them.

✉️ Have tips or tools to share? Reply and contribute to our next edition.

Cheers,

Merlyn Shelley

Growth Lead, Packt

Join us on July 19 for a 150-minute interactive MCP Workshop. Go beyond theory and learn how to build and ship real-world MCP solutions. Limited spots available! Reserve your seat today.

🔶 Introducing MCP Support for Real-Time Intelligence (RTI): Microsoft Fabric RTI now supports Model Context Protocol (MCP), enabling AI agents to access real-time data, run natural language queries, and integrate easily via open APIs. With schema discovery, plug-and-play setup, and future expansions like digital twins and proactive insights, MCP brings powerful, AI-driven analytics to real-time intelligence workflows.

🔶 Use Graph Machine Learning to detect fraud with Amazon Neptune Analytics and GraphStorm: Amazon Neptune Analytics and GraphStorm empower fraud detection by combining scalable graph analytics with graph machine learning. Using Graph Neural Networks, the solution uncovers hidden fraud networks, predicts risk scores, and enriches transaction graphs with embeddings. This pipeline, deployable via SageMaker, enables real-time, dynamic analysis of evolving fraud behaviors.

🔶 Understanding BigQuery enhanced vectorization: Google BigQuery’s enhanced vectorization, now in preview, redefines query performance by leveraging SIMD processing, advanced data encodings, and parallel execution. Tight integration with Capacitor enables faster joins, aggregations, and filter pushdowns. Real-world benchmarks show up to 21× speedups, delivering major gains in efficiency. Full rollout and Parquet support coming soon!

🔶 How to make your SQL scalar user-defined function (UDF) inlineable in Microsoft Fabric Warehouse? Microsoft Fabric now supports inline scalar UDFs in Warehouse preview, improving performance by reducing execution overhead. This post highlights common inlining blockers like non-deterministic functions, complex query usage, and multiple return statements, with guidance on how to refactor them. Broaden SQL compatibility and efficiency through inline-friendly UDF design practices.

🔶 Introducing Continuous Integration for Looker: Looker now offers Continuous Integration (CI) in preview, giving developers tools to improve speed, accuracy, and confidence in deploying LookML code. CI validates LookML, detects SQL and content issues early, and integrates with pull requests or schedules. This helps teams catch errors before production, ensuring reliable and consistent data experiences.

🔶 Recovering data in SQL Server without full backup: When full backups fail, SQL Server's transaction logs can help recover deleted data. This guide walks through using fn_dump_dblog to extract deleted rows from .trn files, even without a full backup. It’s a complex but powerful recovery method that reveals deep insights into SQL Server internals and storage behavior.

🔶 Fabric Eventhouse now supports Eventstream Derived Streams in Direct Ingestion mode (Preview): Microsoft Fabric now supports direct ingestion of derived streams into Eventhouse, enabling seamless, no-code real-time data routing. Users can configure this from the Eventstream canvas, Embedded Real-Time Hub, or Eventhouse Get Data Wizard. Derived streams, created through transformations, can now be ingested directly into KQL tables. This feature is currently in Preview.

🔶 The Hidden Cost of MAXDOP: CPU Spikes, Query Slowdowns, and What We Learned. Hardcoding MAXDOP 4 in queries boosted individual performance but caused CPU contention and system-wide slowdowns. Testing revealed that higher MAXDOP reduces concurrency on limited-core systems. The real fix came from proper indexing and statistics updates, cutting query time from 20 to 1 second. Always tune first before applying parallelism.

🔶 From code to community: The collective effort behind SQL Server 2025. SQL Server 2025 is now in public preview, bringing AI integration, vector search, zero-ETL analytics via Fabric mirroring, and powerful developer features like JSON and regex support. Designed for cloud agility and built through deep community collaboration, it’s the most transformative SQL Server release in over a decade.

🔶 Transforming B2B intelligence: Tradeshift’s journey with Amazon QuickSight and Amazon Q.Tradeshift transformed its B2B analytics by embedding Amazon QuickSight and Amazon Q into its platform, enabling scalable, AI-powered insights for buyers and sellers. This shift replaced a limited in-house tool, reduced engineering overhead, and empowered users to explore data through natural language, redefining how intelligence is delivered across their global e-invoicing network.

🔶 Building an SQL to DataFrame Converter With ANTLR: ANTLR enables seamless SQL-to-DataFrame translation by parsing SQL syntax into structured trees, which can be programmatically converted into Pandas or Spark code. This approach tackles key challenges like syntax differences, execution models, and feature gaps. With proper grammar, visitors, and dialect handling, developers can automate and scale query conversion across frameworks.

🔶 PostgreSQL: pgSCV 0.14.1 released! This PostgreSQL monitoring agent adds support for pg_stat_ssl, pg_stat_subscription, and new pg_stat_io metrics. It also updates Grafana dashboards, Go, and Alpine Linux. Designed for Prometheus compatibility, pgSCV continues to evolve as a unified exporter for PostgreSQL environments. Full details on GitHub.

🔶 MySQL Orchestrator Failover Behavior During Replication Lag: Managing MySQL replication failovers becomes more resilient with orchestrator settings like FailMasterPromotionIfSQLThreadNotUpToDate, DelayMasterPromotionIfSQLThreadNotUpToDate, and FailMasterPromotionOnLagMinutes. These options offer fine-grained control over failover behavior, ensuring consistency by preventing or delaying master promotions when replicas are lagging, ultimately balancing availability and data integrity during outages or transitions.

See you next time!