Azure - DriveDataScience

Real-Time Analytics Deep Dive: Window Types, Accelerated Shortcuts, KQL Functions, Materialized Views, and Eventhouse Optimization

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Deep dive into Fabric Real-Time Analytics. Five window types with KQL examples: tumbling, hopping, sliding, session, snapshot. Accelerated vs standard shortcuts in KQL databases. Advanced KQL functions for dates, strings, aggregations, and JSON parsing. Materialized views for pre-computed aggregations. Eventhouse optimization: retention policies, caching policies, partitioning. RTI error resolution table.

Real-Time Analytics Deep Dive: Window Types, Accelerated Shortcuts, KQL Functions, Materialized Views, and Eventhouse Optimization Read More »

Fabric Warehouse Advanced: COPY INTO, CTAS, Dynamic Management Views, Query Insights, Visual Query Editor, SSMS Connectivity, and T-SQL with Notebooks

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Advanced Fabric Warehouse capabilities. COPY INTO for bulk loading from CSV and Parquet. CTAS for materialized summaries and snapshots. Dynamic Management Views for active queries and sessions. Query Insight views for performance analysis. Visual Query editor for no-code analysis. SSMS and Azure Data Studio connectivity with GRANT/DENY. Integrating T-SQL with Spark notebooks via cross-database queries. Warehouse optimization with statistics, result set caching.

Fabric Warehouse Advanced: COPY INTO, CTAS, Dynamic Management Views, Query Insights, Visual Query Editor, SSMS Connectivity, and T-SQL with Notebooks Read More »

Spark Structured Streaming in Fabric: Stateless vs Stateful Transformations, Checkpoints, Output Modes, Windowing, and Processing Real-Time Data with Delta Lake

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Complete Spark Structured Streaming guide. Streaming vs batch same API, reading from Event Hubs, Delta Lake, and files. Output modes (Append, Complete, Update). Checkpoint location for crash recovery. Stateless vs stateful transformations. Windowing: tumbling, sliding/hopping, session windows with watermarks for late data. Writing to Delta tables and foreachBatch MERGE pattern. Trigger modes including availableNow for pipeline scheduling. Three real-world scenarios.

Spark Structured Streaming in Fabric: Stateless vs Stateful Transformations, Checkpoints, Output Modes, Windowing, and Processing Real-Time Data with Delta Lake Read More »

Fabric REST APIs: Programmatic Management, Automating Workspace Setup, Triggering Pipelines, and Building Admin Scripts in Python

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Complete Fabric REST APIs guide. Authentication three ways (Azure AD app, Azure CLI, mssparkutils). Core endpoints: workspace CRUD, item management, pipeline execution and monitoring, lakehouse table operations, capacity management. Six real-world Python scripts: create workspace with items, trigger and monitor pipeline from external system, audit all items across workspaces (CSV export), bulk assign roles, monitor pipeline failures, export table list. GitHub Actions CI/CD integration. Rate limits and best practices.

Fabric REST APIs: Programmatic Management, Automating Workspace Setup, Triggering Pipelines, and Building Admin Scripts in Python Read More »

Data Activator in Microsoft Fabric: Set Alerts on Your Data, Trigger Actions Automatically, and Monitor Without Building Dashboards

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Master Data Activator (Reflex) in Fabric. Why dashboards are not enough (security camera vs motion sensor analogy). Core concepts (objects, properties, triggers, actions). Setting up from Power BI, Eventstream, and Fabric items. Trigger types: threshold, percentage change, absence, complex AND/OR conditions. Actions: email, Teams, Power Automate, start pipeline, webhook. Six real-world scenarios (inventory monitoring, revenue drop, IoT temperature, pipeline failure watchdog, churn early warning, data quality). Alert fatigue prevention. Comparison with Pipeline alerts and Power BI alerts.

Data Activator in Microsoft Fabric: Set Alerts on Your Data, Trigger Actions Automatically, and Monitor Without Building Dashboards Read More »

OneLake Deep Dive: Architecture, ADLS Gen2 Compatibility, OneLake File Explorer, Multi-Cloud Shortcuts, Storage Billing, and the Foundation of Microsoft Fabric

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Understand the foundation of Fabric. OneLake vs ADLS Gen2 vs S3 comparison, the hierarchy (tenant, workspace, item, tables, files), ADLS Gen2 API compatibility (same API, different endpoint), accessing from Azure Storage Explorer, AzCopy, Python SDK, and external Databricks. OneLake File Explorer for Windows. Multi-cloud shortcuts with caching. Data Hub for discovery. Storage billing details, soft delete, VACUUM for optimization. Three real-world patterns (centralized, hub-and-spoke, multi-cloud unified).

OneLake Deep Dive: Architecture, ADLS Gen2 Compatibility, OneLake File Explorer, Multi-Cloud Shortcuts, Storage Billing, and the Foundation of Microsoft Fabric Read More »

Apache Spark in Fabric: Runtime Configurations, Starter Pools, Custom Environments, V-Order, Adaptive Query Execution, and Performance Tuning

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Open the Spark black box. Driver and executors explained, starter pools vs custom environments, key configurations (shuffle partitions with pizza analogy, AQE autopilot, auto-optimize, auto-compact, V-Order), broadcast joins, memory management, reading the Spark UI to identify bottlenecks (skew, small files, shuffles), four performance tuning patterns (small data, large data, join, write optimization), Spark Job Definitions for production, and high concurrency mode.

Apache Spark in Fabric: Runtime Configurations, Starter Pools, Custom Environments, V-Order, Adaptive Query Execution, and Performance Tuning Read More »

Fabric Administration and Cost Management: Capacity Units, Throttling, Smoothing, Monitoring, Pause and Resume, and Optimizing Your Fabric Spend

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Master Fabric cost management. Capacity Units explained, F-SKU sizing guide (F2 to F512 with prices), CU consumption by workload type, throttling mechanics (10-min, 60-min, 24-hr windows), smoothing and burst model, monitoring with Capacity Metrics app, pause and resume automation, five cost optimization strategies (right-size, optimize Spark, stagger pipelines, pause dev, optimize Delta), and real-world sizing scenarios.

Fabric Administration and Cost Management: Capacity Units, Throttling, Smoothing, Monitoring, Pause and Resume, and Optimizing Your Fabric Spend Read More »

Fabric Security and Governance: Workspace Roles, OneLake Data Access, Item Permissions, Sensitivity Labels, Purview Integration, and Data Lineage

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Every Fabric security layer explained. Seven layers from workspace roles to sensitivity labels. Workspace roles matrix (Admin, Member, Contributor, Viewer), item permissions, OneLake data access roles for table-level control, RLS in Warehouse and Semantic Models, CLS with GRANT on specific columns, dynamic data masking, sensitivity labels that flow downstream, Purview integration for lineage and catalog, endorsement (Promoted, Certified), and complete real-world security architecture.

Fabric Security and Governance: Workspace Roles, OneLake Data Access, Item Permissions, Sensitivity Labels, Purview Integration, and Data Lineage Read More »

Power BI in Fabric: Direct Lake, Semantic Models, Import vs DirectQuery vs Direct Lake, and Connecting Your Data to Reports

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Master Direct Lake in Fabric. Three connection modes compared (Import vs DirectQuery vs Direct Lake), how Direct Lake reads Delta files directly from OneLake, when it falls back to DirectQuery with guardrail thresholds, semantic models (auto-generated vs custom), building relationships and DAX measures, connecting Power BI Desktop, RLS with Direct Lake, V-Order optimization, and end-to-end pipeline-to-dashboard scenario.

Power BI in Fabric: Direct Lake, Semantic Models, Import vs DirectQuery vs Direct Lake, and Connecting Your Data to Reports Read More »