Search, Graph & Observability Engineering Mastery Pack

With its practical approach and real-world examples, this essential resource explores the full potential of Elastic Stack for data-driven projects. Learn how to build scalable and efficient data analytics and search solutions using Elastic Stack.

This book will guide you through the core components of the Elastic Stack and how they work together to solve your data problems. You'll look at how the stack can be best leveraged to build and deliver powerful solutions to tackle real-world search, observability, and cybersecurity use cases.

Master OpenSearch with this expert-led guide, covering installation, data ingestion, queries, dashboards, and performance optimization through hands-on tutorials and real-world examples.

Unlock the full potential of Splunk Enterprise with this comprehensive guide by following the admin exam blueprint, from installation to advanced techniques, all in one place. Packed with practical examples, the guide simplifies learning and allows you to master the platform's capabilities easily and get certified as a Splunk Enterprise admin.

Cypher is a great language to express graph traversals, but it still requires a bit of change in the thinking process to write performant cypher queries. This book will help to get the best out of neo4j using cypher language and its capabilities.

Graph Data Modeling with Python is your guide to building real-world use cases of how to prepare graph data for modeling, converting tabular to graph data structures, and working through simple graph use cases using degree centrality. Using the Python packages igraph and NetworkX, you'll build your skills in various types of graph analytics.

This pioneering guide to the new ISO-standardized Graph Query Language (GQL) will help you modify, query, and analyze graph data using foundational and advanced concepts, as well as practice with sample codes on the GQL Playground.