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Full Description
Turn the avalanche of raw data from Azure Data Explorer, Azure Monitor, Microsoft Sentinel, and other Microsoft data platforms into actionable intelligence with KQL (Kusto Query Language). Experts in information security and analysis guide you through what it takes to automate your approach to risk assessment and remediation, speeding up detection time while reducing manual work using KQL. This accessible and practical guide—designed for a broad range of people with varying experience in KQL—will quickly make KQL second nature for information security.
Solve real problems with Kusto Query Language— and build your competitive advantage:
Learn the fundamentals of KQL—what it is and where it is used
Examine the anatomy of a KQL query
Understand why data summation and aggregation is important
See examples of data summation, including count, countif, and dcount
Learn the benefits of moving from raw data ingestion to a more automated approach for security operations
Unlock how to write efficient and effective queries
Work with advanced KQL operators, advanced data strings, and multivalued strings
Explore KQL for day-to-day admin tasks, performance, and troubleshooting
Use KQL across Azure, including app services and function apps
Delve into defending and threat hunting using KQL
Recognize indicators of compromise and anomaly detection
Learn to access and contribute to hunting queries via GitHub and workbooks via Microsoft Entra ID
Contents
Foreword by Ann Johnson
CHAPTER 1 Introduction and Fundamentals
CHAPTER 2 Data Aggregation
CHAPTER 3 Unlocking Insights with Advanced KQL Operators
CHAPTER 4 Operational Excellence with KQL
CHAPTER 5 KQL for Cybersecurity—Defending and Threat Hunting
CHAPTER 6 Advanced KQL Cybersecurity Use Cases and Operators
