Launching at RSA Conference: Aembit is introducing its Identity Federation Hub, a breakthrough for securing non-human identities (NHIs) like apps, AI agents, and service accounts, without using long-lived secrets.

Instead of spreading static credentials across clouds, Aembit acts as a short token service that brokers identity-based access across AWS, Azure, GCP, and SaaS platforms. Think of it as "MFA for machines", dynamic, posture-aware access with no code changes for developers.

✅ No secret sprawl
✅ No custom auth logic
✅ Just-in-time, cross-cloud access control

With support from Snowflake and others, Aembit is redefining what it means to enforce Zero Trust at scale for workloads. Learn how they’re making identity-first access practical in today’s multi-cloud, AI-driven world.

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Welcome to this edition of BIPro #99, where we bring together the most practical breakthroughs and real-world strategies shaping the future of analytics, databases, and AI-powered data workflows.

This issue is packed with insights that help you go beyond charts and dashboards, from streamlining Jira project reporting with generative BI in Amazon QuickSight, to debugging Python smarter, and building AI agents on real-time Oracle data.

Highlights include:

✅ AI-assisted database troubleshooting with Cloud SQL and AlloyDB

✅ Fabric Copilot turning natural language into T-SQL

✅ BigQuery ML’s contribution analysis now GA for automated trend detection

✅ Low-code AI in notebooks and Data Wrangler

✅ Python essentials like decorators and debugging techniques you’ll actually use

✅ Oracle to OneLake replication without the ETL headache

✅ Data Analyst GPT to clean, cluster, and model without code

Whether you're a data engineer, analyst, or architect, this roundup helps you stay sharp and ship smarter in the AI-driven data era.

Let’s dive in.

Cheers

Merlyn Shelley

Growth Lead, Packt

📌 Unlock data insights from custom Jira projects using generative BI in Amazon QuickSight: Extract insights, streamline reporting, and visualize Jira data with Amazon QuickSight’s generative BI. This blog shows how to integrate AWS services to automate the flow from Jira to dashboards, making it easier to analyze custom fields, track project progress, and empower teams with real-time, actionable project management data.

📌 Inside AI assisted troubleshooting for databases: Troubleshoot smarter, optimize faster, and manage databases with confidence using AI-assisted tools in Cloud SQL and AlloyDB. This blog shows how generative AI simplifies root-cause analysis, predicts query issues, and delivers clear recommendations, empowering developers to maintain performance without deep database expertise, and accelerating development in modern DevOps environments.

📌 BigQuery ML contribution analysis models now GA: Pinpoint drivers, uncover trends, and act on insights with BigQuery ML’s contribution analysis. This blog explores how to automate multidimensional analysis at scale, helping you identify what’s influencing key metrics like sales drops or user behavior. With new features, it's faster and easier to surface impactful patterns across complex datasets.

📌 Query vs. Mutation in API for GraphQL – Understanding the difference: Build smarter APIs, fetch data efficiently, and update systems with precision using API for GraphQL in Microsoft Fabric. This blog breaks down the difference between queries and mutations, shows how to enable or disable them dynamically, and explains how GraphQL simplifies interaction with various Fabric-supported data sources for modern development.

📌 Evaluate your Fabric Data Agents programmatically with the Python SDK (Preview): Evaluate agents, test accuracy, and improve responses using the new Fabric SDK preview for Data Agents. This blog walks through running structured evaluations from notebooks or pipelines, letting you define ground truth, apply custom prompts, and view performance metrics. Perfect for fine-tuning and validating Data Agents before production deployment.

📌 Announcing Copilot for SQL Analytics Endpoint in Microsoft Fabric (Preview): Query data, explore insights, and generate SQL instantly with Copilot for SQL Analytics Endpoint in Microsoft Fabric. This AI-powered assistant converts natural language into optimized T-SQL across Lakehouses, Warehouses, and mirrored databases, streamlining complex queries and accelerating analytics. Now in preview, it brings speed, clarity, and confidence to everyday data work.

📌 Fabric April 2025 Feature Summary: Explore new AI tools, streamline migrations, and enhance performance with Microsoft Fabric’s April 2025 updates. Highlights include low-code AI in notebooks, session-scoped temp tables, a built-in migration assistant for Data Warehouse, and Copilot access on all paid SKUs, empowering users across roles to move faster, work smarter, and deliver more value.

📌 Custom Python Decorator Patterns Worth Copy-Pasting Forever: Boost performance, debug smarter, and write cleaner Python with these five powerful decorator patterns. This blog walks through memoization, logging, timing, and retry logic, with real examples and code snippets. Whether you're optimizing workflows or simplifying diagnostics, these reusable patterns can streamline how you write and manage Python functions.

📌 7 Python Debugging Techniques Every Beginner Should Know: Debug faster, fix smarter, and code with confidence using these 7 beginner-friendly Python debugging techniques. From smarter print statements to using assertions and reading stack traces effectively, this blog shares practical tips to help you catch bugs early, understand common pitfalls, and improve your problem-solving instincts as a Python developer.

📌 Accelerate AI on Oracle Databases with Open Mirroring, Fabric Data Agent, and Azure AI Foundry: Replicate Oracle data, build data agents, and power AI insights with Microsoft Fabric and Azure AI Foundry. This blog shows how Open Mirroring and Oracle GoldenGate integration streamline real-time data flow into OneLake, enabling AI-driven analytics with Fabric’s data agents and Azure AI agents, without heavy ETL or complex SQL.

📌 Data Analyst AI tool: Clean datasets, explore trends, and build models using the Data Analyst GPT in ChatGPT. This blog walks through hands-on steps, from loading and cleaning Titanic data to generating visualizations, clustering, and logistic regression, all without writing code. Perfect for analysts looking to speed up insights with AI-driven workflows.

📌 Temporary Tables in a Microsoft Fabric Warehouse: Explore limitations, troubleshoot performance, and rethink temporary tables in Microsoft Fabric Warehouse. This blog highlights gaps in Fabric’s temp table support compared to SQL Server, walks through a demo with alternative techniques, and offers practical workarounds to handle intermediate result sets efficiently in today’s distributed Fabric environment.