Azure Data Explorer for Real-Time Big Data Analytics

Organizations today generate massive volumes of telemetry, log, and time-series data that must be analyzed in real time to make critical business decisions. This text-based course provides a comprehensive introduction to Azure Data Explorer (ADX), a fast and highly scalable data analytics service designed for rapid ad-hoc querying. You will transition from understanding core big data concepts to writing powerful queries that extract actionable insights from complex datasets. What you'll learn: - Understand the foundational architecture of Azure Data Explorer and its primary use cases - Write efficient queries using Kusto Query Language (KQL) to filter, summarize, and join data - Configure data ingestion pipelines for both streaming and batch data sources - Analyze structured, semi-structured, and unstructured log formats with ease - Apply best practices for database schema design, caching, and data retention policies - Evaluate ADX performance and cost-effectiveness for your organization's big data workloads You will begin by exploring fundamental terminology, database structures, and the core components of the engine. From there, you will progress through structured text lessons covering KQL syntax, data ingestion strategies, and performance optimization techniques, complete with practical code snippets and written exercises. This course is designed for data analysts, cloud engineers, and IT professionals who are new to Azure Data Explorer and want to evaluate its capabilities. No prior experience with KQL or cloud data warehousing is required. Start reading today to master the essentials of real-time big data analytics.