Evaluate and Optimize Enterprise Log Analytics

By the end of this course, learners will be able to configure Windows and agentless inputs, ingest data using multiple Splunk methods, parse and normalize events accurately, manage timestamps and time zones, and classify data effectively for reliable analysis. This hands-on, project-focused course is designed to help learners build strong, practical expertise in Windows data ingestion and processing using Splunk. You will explore Windows-specific inputs, agentless collection techniques, HTTP Event Collector (HEC), and PowerShell-based data ingestion, gaining a clear understanding of when and why to use each approach. The course also dives deep into parsing fundamentals, including event boundaries, multi-line events, timestamp extraction, and the use of props.conf for data transformations. Learners benefit by developing job-ready skills that are directly applicable to real-world Splunk environments, especially those managing complex Windows infrastructures. What makes this course unique is its end-to-end project orientation: rather than isolated concepts, you will see how inputs, parsing, metadata, and classification work together in a complete data onboarding workflow. This structured, practical approach ensures you can confidently design, troubleshoot, and optimize Splunk data ingestion pipelines in professional settings.

By the end of this course, learners will be able to automate Splunk reports, design interactive dashboards, apply reusable macros, build structured data models, and generate high-performance visual analytics using pivots and acceleration techniques. This course provides a comprehensive, hands-on pathway for mastering Splunk reporting and data modeling beyond basic search usage. Learners will gain practical skills to schedule and manage reports, create dynamic dashboards, and standardize search logic using macros. Through structured lessons on data models, attributes, lookups, and hierarchies, participants will learn how to simplify complex data and enable self-service analytics for stakeholders. What makes this course unique is its end-to-end, job-focused approach. Instead of isolated features, learners experience how reports, dashboards, macros, data models, and pivots work together in real-world scenarios. Performance optimization through data model acceleration and instant pivots ensures learners can deliver insights quickly and efficiently. By completing this course, learners will improve operational visibility, reduce repetitive work, and confidently design scalable Splunk solutions—making them more effective analysts, engineers, and Splunk power users.

By completing this course, learners will be able to analyze Splunk’s access control architecture, implement role-based security, configure enterprise authentication mechanisms, and evaluate authentication workflows for secure data access. Learners will develop the skills required to manage users, roles, capabilities, and authentication methods in real-world Splunk environments. This course provides a comprehensive, hands-on exploration of Splunk Authentication and Access Control, moving from foundational role and index permissions to advanced enterprise integrations such as LDAP, SAML-based single sign-on, reverse proxy logout, and scripted authentication. Through structured modules and practical demonstrations, learners gain a deep understanding of how Splunk enforces security, controls data visibility, and integrates with external identity providers. What makes this course unique is its end-to-end security focus, combining conceptual understanding with implementation-driven learning. Rather than treating authentication as a standalone topic, the course connects roles, capabilities, indexes, and authentication into a single cohesive security model. This approach prepares learners to confidently design, troubleshoot, and optimize Splunk authentication strategies. The course is ideal for Splunk administrators, security analysts, and IT professionals who want to strengthen Splunk security, support enterprise authentication standards, and manage user access at scale.

Learners will configure, analyze, and manage Splunk configuration files, indexes, and data lifecycle processes to ensure efficient, reliable, and compliant data operations. By the end of this course, learners will be able to apply configuration precedence rules, troubleshoot merge conflicts, manage indexes and retention policies, and monitor indexing activities in real-world Splunk environments. This course provides hands-on, project-oriented learning focused on Splunk configuration architecture and index management—two critical skills for Splunk administrators and data engineers. Learners gain practical experience working with configuration directories, index-time and search-time processing, btool validation, index sizing, retention strategies, backups, and data recovery. Each module builds progressively, connecting foundational concepts with advanced operational practices used in production Splunk deployments. What makes this course unique is its end-to-end focus on how configuration decisions directly impact data storage, performance, and reliability. Rather than treating configuration and indexing as isolated topics, the course integrates them into a complete operational workflow. Upon completion, learners will be well-prepared to manage Splunk environments confidently, reduce configuration errors, optimize storage usage, and support scalable, enterprise-grade data platforms.

Learners will analyze Splunk performance bottlenecks, apply indexing and search optimization techniques, and evaluate system behavior in both small and large-scale environments. By the end of the course, learners will be able to optimize data pipelines, configure index parallelization, improve search and report performance, manage real-time and parallel searches, and use diagnostic tools to maintain system stability. This course equips learners with practical skills to enhance Splunk performance across the entire data lifecycle—from ingestion and indexing to searching, reporting, and enterprise deployment. Learners will gain hands-on insight into optimizing index storage, scheduling searches effectively, controlling search jobs, and tuning queries to reduce runtime and resource consumption. Advanced topics such as real-time search optimization, log level management, and large-scale Splunk architecture planning are also covered. What makes this course unique is its project-oriented, performance-first approach grounded in real operational scenarios. Instead of focusing only on Splunk features, the course emphasizes measurable performance improvements, scalability planning, and troubleshooting strategies used in production environments. This makes the course especially valuable for data engineers, Splunk administrators, and analysts aiming to build reliable, high-performing Splunk platforms.