Exploring Data in Microsoft Azure Using Kusto Query Language and Azure Data Explorer
Data teams are drowning in Azure logs and metrics—but most lack the query skills to extract actionable insights fast. This course teaches you Kusto Query Language (KQL) and Azure Data Explorer, the tools Microsoft uses internally to analyse petabytes of data. You’ll move from SQL-adjacent syntax to production-ready queries in under 3 hours.
AIU.ac Verdict: Essential for cloud engineers, data analysts, and DevOps professionals who need to query Azure data without waiting for data engineers. The course is hands-on and vendor-backed, though it assumes basic familiarity with databases or log analysis—pure beginners may need a SQL primer first.
What This Course Covers
You’ll start with KQL fundamentals: syntax, operators, and the tabular data model that makes Azure Data Explorer fast. Then move into real-world scenarios—filtering massive datasets, aggregating metrics, detecting anomalies, and building dashboards. The course includes sandbox labs where you query actual Azure telemetry, so you’re not just learning syntax; you’re solving problems you’ll face on day one.
Specific topics include data ingestion workflows, time-series analysis for monitoring, join operations across multiple tables, and visualisation techniques. By the end, you can write complex queries to troubleshoot infrastructure, audit security logs, and generate compliance reports—skills that directly reduce mean-time-to-resolution (MTTR) in cloud operations.
Who Is This Course For?
Ideal for:
- Cloud & DevOps Engineers: Need KQL to query Azure Monitor logs, Application Insights, and diagnostic data without escalating to data teams.
- Data Analysts & BI Professionals: Expanding into Azure ecosystem and need a fast, modern query language that scales better than traditional SQL for cloud-native data.
- Security & Compliance Officers: Must audit and analyse Azure activity logs, threat detection data, and security events—KQL is the native tool for this.
May not suit:
- SQL-Only Practitioners: If you’ve never written a WHERE clause or aggregated data, start with SQL fundamentals first; this assumes query literacy.
- Non-Azure Users: KQL is Azure-specific. If your organisation uses AWS or GCP exclusively, this won’t transfer directly to your stack.
Frequently Asked Questions
How long does Exploring Data in Microsoft Azure Using Kusto Query Language and Azure Data Explorer take?
2 hours 45 minutes of video content. Most learners complete it in one or two sittings, though hands-on labs may add 1–2 hours depending on depth.
Do I need Azure experience before starting?
No, but you should be comfortable with basic database concepts (tables, rows, filtering). If you’ve used SQL or any query language, you’re ready.
Will I have access to a real Azure environment to practise?
Yes. Pluralsight includes sandbox labs where you query live Azure Data Explorer instances, so you’re not just watching—you’re hands-on from day one.
Is this course enough to use KQL in production?
For most common scenarios—log analysis, alerting, dashboards—yes. For advanced scenarios (custom plugins, optimisation at scale), you may need supplementary resources, but the fundamentals are solid.
Course by Neeraj Kumar on Pluralsight. Duration: 2h 45m. Last verified by AIU.ac: March 2026.
