using-dbt-for-analytics-engineering

Execute KQL queries and analyze data in Azure Data Explorer for log analytics, telemetry, and time series insights. Execute KQL queries against massive datasets with sub-second performance, including filtering, aggregation, time series analysis, and cross-table joins Discover and explore cluster resources, databases, and table schemas to understand your data model before querying Supports five core query patterns: basic retrieval, aggregation analysis, time series analytics, join-based correlation, and schema discovery Built-in fallback to Azure CLI commands when MCP tools timeout or encounter connection errors

Identify cost savings across Azure subscriptions through resource analysis, utilization metrics, and actionable optimization recommendations. Discovers orphaned resources (unattached disks, unused NICs, idle gateways) and over-provisioned services using Azure Quick Review Queries actual costs from Azure Cost Management API and utilization data from Azure Monitor to support rightsizing recommendations Generates prioritized optimization reports with estimated savings, implementation commands, and Azure Portal links for each resource Includes specialized Redis cost optimization analysis with subscription filtering and pre-built report templates Requires Cost Management Reader, Monitoring Reader, and Reader roles; validates prerequisites before analysis begins

日程待办摘要：编排 calendar +agenda 和 task +get-my-tasks，生成指定日期的日程与未完成任务摘要。适用于了解今天/明天/本周的安排。

Unified Azure cost management: query historical costs, forecast future spending, and optimize to reduce waste. WHEN: \"Azure costs\", \"Azure spending\",…