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Welcome to BIPro #102 – Smarter, Sharper, AI-First BI
From zero-ETL breakthroughs to smarter debugging in Fabric, this issue is packed with forward-looking updates that make your BI practice leaner and more intelligent. Whether you're exploring transactional BigQuery features, debugging user data functions locally, or scaling agentic AI, these updates give you the tools to stay ahead in an increasingly AI-driven analytics landscape.
Key Highlights:
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💡 Whether you’re scaling AI in your stack or still fighting dashboard fatigue, this week’s BIPro is packed with insights to move your strategy forward.
Helping you close the gap between data and action.
Cheers,
Merlyn Shelley
Growth Lead, Packt
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🔷 Understanding updates to BigQuery workload management: Boost BigQuery Efficiency. Google’s June 2025 update enhances BigQuery workload management with fairer slot allocation, reservation predictability, autoscaler granularity, runtime reservation targeting, and detailed cost labeling. These updates improve performance, cost control, and scalability, empowering BI teams to manage compute resources more intelligently for consistent, optimized data analytics at scale.
🔷 BigQuery features for transactional data management: BigQuery Evolves Beyond Analytics. Google’s latest update brings transactional power to BigQuery. Highlights include fine-grained DML for efficient data edits, CHANGES TVF for row-level change tracking, and real-time DML on streaming data. These features streamline dynamic data management, cutting costs, reducing latency, and simplifying architectures for responsive, analytics-integrated applications.
🔷 Refresh SQL analytics endpoint Metadata REST API (Preview): Refresh SQL Endpoint Metadata On-Demand: Microsoft Fabric now enables API-based table metadata refresh for SQL analytics endpoints. Gain synchronous/asynchronous control, real-time sync status, error diagnostics, and timeout customization. This streamlines data validation, enhances workflow precision, and ensures up-to-date metadata for accurate, responsive analytics across your Fabric workspace.
🔷 How to Perform a Disaster Recovery Switchover with Patroni for PostgreSQL? Ensure PostgreSQL Resilience with Patroni DR Switchover: Learn how to perform a disaster recovery switchover using Patroni for PostgreSQL. This guide covers DC-DR cluster setup, real-time failover management, and safe primary-to-standby transitions. Streamline HA/DR operations, minimize downtime, and safeguard data continuity across distributed environments using Patroni and AnyDBver.
🔷 AI Agents: The Protocol Revolution Driving Next-Gen Enterprise Intelligence. Agentic AI Standards Take Shape: New protocols, MCP, ACP, and A2A, are accelerating enterprise adoption of agentic AI. These standards simplify agent collaboration, cross-platform integration, and real-time context building. With growing vendor support, including Couchbase and Google, developers can now build scalable, intelligent, multi-agent systems more easily, ushering in AI’s next enterprise phase.
🔷 Techniques to query Azure SQL’s new JSON Datatype: Azure SQL Embraces Native JSON: Azure SQL’s new JSON datatype and functions (including JSON_ARRAYAGG, JSON_OBJECTAGG) simplify structured JSON handling. Benefits include native constraints for data validation, powerful aggregation, and dynamic pivoting. These enhancements streamline semi-structured data analytics, boost SQL Server 2025 readiness, and align with ANSI SQL:2016 standards.
🔷 Simplify real-time analytics with zero-ETL from Amazon DynamoDB to Amazon SageMaker Lakehouse: Zero-ETL for Real-Time Insights: AWS introduces zero-ETL integration from DynamoDB to SageMaker Lakehouse. This no-code setup enables real-time analytics and ML on NoSQL data, without ETL pipelines. With CDC-based syncing, Apache Iceberg support, and SageMaker Unified Studio access, enterprises can drive faster, scalable decision-making from operational data.
🔷 Pub/Sub single message transforms: Streamline Real-Time Data with Pub/Sub SMTs: Google Cloud introduces Pub/Sub Single Message Transforms (SMTs), starting with JavaScript UDFs. Perform lightweight in-stream transformations, like redaction, format conversion, and filtering, directly in Pub/Sub. This reduces latency, simplifies architecture, and enhances flexibility for BI teams needing real-time insights without extra processing infrastructure.
🔷 How to debug user data functions locally in VS Code? Accelerate Fabric Function Development with Local Debugging: Microsoft Fabric now supports local debugging for user data functions in VS Code. Developers can write, test, and troubleshoot Python-based SQL operations safely without impacting live environments. Breakpoints, logs, and Fabric extensions enhance function validation, boosting efficiency in building robust, data-driven BI workflows.
🔷 Secure Your Data from Day One: Best Practices for Success with Purview Data Loss Prevention (DLP) Policies in Microsoft Fabric. Secure Fabric Data with Purview DLP Best Practices: Microsoft Fabric now offers enhanced Data Loss Prevention (DLP) via Purview. From classifying sensitive data to refining policy scopes and empowering teams, these strategies help protect OneLake data, ensure compliance, and foster responsible data use, establishing a secure foundation for scalable analytics.
🔷 SQL Automate - A DBA's Time-Saving Toolkit: Optimize SQL Server Deployments with SQL Automate: SQL Automate is a PowerShell-based toolkit that simplifies and speeds up SQL Server installation and post-configuration tasks. From database setup to TempDB tuning and firewall rules, DBAs can save time, reduce manual errors, and focus on strategic work with this efficient, modular automation tool.
🔷 How to Sort Combo Box Values in a Power Apps Canvas App? Enhance Power Apps UX with Sorted Combo Boxes: Sorting Combo Box and Drop Down values in Power Apps boosts usability. This guide shows how to alphabetically or numerically sort SharePoint list-driven fields using formulas like Sort and SortByColumns, ensuring cleaner, more intuitive interfaces in forms and data-driven canvas apps.
🔷 Top 5 Things You Should Know About Azure Data Factory: Master Azure Data Factory Fundamentals: With three ADF versions, Azure, Synapse, and Fabric, understanding their differences is essential. This guide covers key distinctions, connection management quirks, and pricing basics. Whether you're onboarding teammates or migrating workloads, these insights help you navigate ETL/ELT orchestration and cost-efficient pipeline development across Microsoft's evolving data platforms.
See you next time!