Elastic Analyst

This three day, instructor led Elastic Analyst certification is an industry-recognized credential that validates an individual’s expertise in leveraging the Elastic Stack to analyze data. It is all about demonstrating proficiency in using Elasticsearch, Kibana, Beats, and Logstash to ingest, search, analyze, and visualize data effectively. Industries use this certification to identify skilled professionals who can turn their data into actionable insights through the Elastic Stack. The certification involves comprehensive assessment on various aspects including data collection with Beats, data processing with Logstash, data storage and retrieval with Elasticsearch, and visualization and data navigation with Kibana. It thus empowers professionals to optimize data analytics and improve decision-making processes. At the completion of this certification course, participants will be able to:

• Define and manage index patterns in Kibana, with and without applying a Time Filter field, to organize and access data efficiently.
• Apply the Kibana Query Language (KQL) to filter and retrieve specific data sets matching various criteria, enhancing search precision.
• Create, customize, and pin filters to refine search results and boost the relevance of data analysis.
• Construct various visualizations including Metric, Gauge, Lens, and others, to represent data in an easily digestible and actionable format.
• Perform advanced visualizations like geo-mapping and Time Series Visual Builder (TSVB) to gain insights from spatial data and time-based patterns.
• Utilize sub-bucket aggregations to split visualizations, allowing for more granular analysis of data segments.
• Implement calculations and aggregations such as moving averages and derivatives within visualizations to identify trends and anomalies.
• Develop comprehensive dashboards that aggregate multiple visualizations into a single view, providing a cohesive analysis experience.
• Explore Machine Learning features within Kibana to set up jobs for anomaly detection and insights into data behavior.
• Create and leverage scripted fields and Space functionalities to extend Kibana’s analytical capabilities and personalize the analysis environment.

• Basic understanding of data structures and common data formats such as JSON
• Familiarity with the concepts of databases and data storage
• Awareness of search engine concepts and principles
• Some exposure to analytics and data visualization
• Basic knowledge of command-line interfaces and operating systems (Windows, Linux, or macOS)
• An elementary understanding of networking principles, including TCP/IP
• Willingness to learn new querying languages, specifically the Kibana Query Language (KQL)

• Data Analysts
• Business Intelligence Professionals
• IT Analysts
• Search and Log Analysis Engineers
• Data Scientists
• Security Analysts (particularly those interested in SIEM)
• DevOps Engineers (involved in monitoring and observability)
• Kibana Users and Dashboard Creators
• Elasticsearch Developers
• Software Engineers who implement Elastic Stack solutions
• System Administrators involved in data indexing and searching
• Network Administrators focusing on real-time data analysis

Module 1 – Searching Data

• Define an index pattern with or without a Time Filter field Set the time filter to a specified date or time range
• Use the Kibana Query Language (KQL) in the search bar to display only documents that match a specified criteria Create and pin a filter based on a search criteria
• Apply a search criteria to a visualization or dashboard

Module 2 – Visualizing Data

• Create a Metric or Gauge visualization that displays a value satisfying a given criteria Create a Lens visualization that satisfies a given criteria
• Create an Area, Line, Pie, Vertical Bar or Horizontal Bar visualization that satisfies a given criteria Split a visualization using sub-bucket aggregations
• Create a visualization that computes a moving average, derivative, or serial diff aggregation Customize the format and colors of a line chart or bar chart
• Using geo data, create an Elastic map that satisfies a given criteria
• Create a visualization using the Time Series Visual Builder (TSVB) that satisfies a given set of criteria Define multiple line or bar charts on a single TSVB visualization
• Create a chart that displays a filter ratio, moving average, or mathematical computation of two fields Define a metric, gauge, table or Top N visualization in TSVB
• Create a Tag Cloud visualization on a keyword field of an index Create a Data Table visualization that satisfies a given criteria Create a Markdown visualization
• Define and use an Option List or Range Slider control
• Create a Dashboard that consists of a collection of visualizations

Module 3 – Analyzing Data

• Answer questions about a given dataset using search and visualizations Use visualizations to find anomalies in a dataset
• Define a single metric, multi-metric, or population Machine Learning job Define and use a scripted field for an index
• Define and use a Space in Kibana