1 min read
Microsoft Fabric Notebooks: Collaborative Data Science at Scale
Fabric notebooks provide a seamless path from exploration to production, with built-in governance, collaboration, and scalable compute.
Blog
Thoughts on data engineering, cloud architecture, and technology. 2205 articles and counting.
Showing 24 of 2205 posts — page 12 of 92
1 min read
Vector Database Selection: Choosing the Right Solution for RAG
The best vector database depends on your specific requirements. Azure AI Search excels for hybrid search with integrated semantic ranking. Pinecone offers…
1 min read
Responsible AI: Content Safety Filters for LLM Applications
Content safety is non-negotiable for production AI applications. Implement multiple layers of filtering for both inputs and outputs to protect users and…
1 min read
Data Mesh: Federated Computational Governance
Computational governance scales where manual review cannot. Embed policies in CI/CD pipelines to catch issues before they reach production.
1 min read
AI Agent Memory: Implementing Long-Term Context
Long-term memory transforms one-shot interactions into ongoing relationships. Users feel understood when the AI remembers their preferences, past issues…
1 min read
Prompt Engineering: System Prompts That Actually Work
Invest time in crafting and testing your system prompts. They are the foundation of consistent, high-quality AI interactions.
1 min read
Microsoft Fabric Data Activator: Event-Driven Data Alerts
Data Activator monitors data streams and triggers actions based on conditions you define. It connects to Power BI reports, Eventstreams, and Fabric data…
1 min read
Azure Document Intelligence: Table Extraction and Analysis
Table extraction transforms static reports into queryable data. Combine extracted tables with LLM analysis to answer questions about financial statements…
1 min read
Enterprise AI: Building Secure API Gateways for LLM Access
A well-designed gateway enables enterprise-wide AI adoption while maintaining security, compliance, and cost control.
1 min read
Semantic Caching for LLM Applications: Reducing Costs and Latency
Unlike exact-match caching, semantic caching uses embeddings to find similar queries even when worded differently.
1 min read
Fine-Tuning with LoRA: Efficient Model Customization
Instead of updating all model weights, LoRA injects trainable low-rank matrices into transformer layers. These adapters capture task-specific knowledge…
1 min read
Responsible AI: Implementing Explainability in Production Models
SHAP (SHapley Additive exPlanations) provides consistent, theoretically grounded feature importance scores.
1 min read
Data Mesh: Implementing Self-Serve Data Infrastructure
A data platform that enables self-service must provide templates, guardrails, and automation while maintaining governance.
1 min read
Multi-Agent Systems: Orchestrating Specialized AI Agents
Multi-agent architectures shine for tasks requiring diverse expertise: research reports, code reviews, complex analysis, and creative projects. The key is…
1 min read
Prompt Engineering: Structured Output with JSON Mode
For even stricter control, use the structured outputs feature with a JSON schema. JSON mode transforms LLMs from conversational tools into reliable data…
1 min read
Microsoft Fabric Lakehouse: Medallion Architecture Implementation
Bronze holds raw ingested data. Silver contains cleansed and conformed data. Gold presents business-level aggregates ready for consumption.
1 min read
Azure Document Intelligence Custom Models: Training for Specialized Documents
Azure offers three custom model approaches: template models for fixed layouts, neural models for varied layouts, and composed models that combine multiple…
1 min read
Enterprise AI Governance: Building Model Registries and Approval Workflows
A model registry serves as the single source of truth for all ML models, tracking versions, lineage, and deployment status.
1 min read
Hybrid Search: Combining Vector and Keyword Search in Azure AI Search
Vector search excels at semantic similarity but can miss exact matches. Keyword search finds precise terms but misses synonyms and context. Together, they…
1 min read
Fine-Tuning GPT Models: When and How to Customize
Fine-tuning makes sense when you need consistent formatting, domain-specific terminology, or significant behavior changes that prompting cannot achieve…
1 min read
Responsible AI: Implementing Fairness Metrics in ML Pipelines
Different fairness definitions apply to different contexts. Demographic parity, equalized odds, and calibration each capture distinct aspects of fairness.
1 min read
Data Mesh Implementation: Domain-Oriented Data Products
Data mesh rests on four pillars: domain ownership, data as a product, self-serve data platform, and federated computational governance.
1 min read
Building AI Agents with Tool Use: A Practical Architecture
At its core, an AI agent follows a simple loop: observe, think, act, repeat. Tools should be focused, well-documented, and handle errors gracefully.
1 min read
Prompt Engineering: Chain-of-Thought Techniques for Complex Reasoning
When faced with multi-step problems, LLMs perform better when prompted to reason step-by-step rather than jump directly to answers.