Analyzing Data

# Analyzing Data
These will provide where to find the documentation if the applicable topic has said documentation and then provide examples for applying said topic.

- Answer questions about a given dataset using search and visualizations
This doesnt have examples nor documentation since it's related to the exam and interpreting a dashboard.

- Use Machine Learning tools to detect anomalies in a dataset
https://www.elastic.co/guide/en/kibana/current/xpack-ml.html
Note: To do this in an environment you built, make sure to upgrade the license for a free trial. 
Example: Detect anomalies in the flught delay time or flight price or flight time dataset.

- Define a single metric, multi-metric, population, or categorization Anomaly Detection job
https://www.elastic.co/guide/en/kibana/current/xpack-ml-anomalies.html
Single-Metric Example:
Multi-Metric Example:
Population Example:
Categorization Example:

- Define and use runtime fields
https://www.elastic.co/guide/en/elasticsearch/reference/current/runtime.html
Example: In the default flight index, create a runtime field called IsInternational.
The IsInternational runtime field should be True if the OrigCountry is not the same as the DestCountry.
After creating that field, then create a visualization that shows how many flights are international flights over a time period. 

- Create a data frame analytics job to detect outliers
https://www.elastic.co/guide/en/kibana/current/xpack-ml-dfanalytics.html
Data Frame Analytics Example:

- Create a transform that generates an entity-centric index
https://www.elastic.co/guide/en/elasticsearch/reference/current/transform-overview.html
Example: https://www.elastic.co/guide/en/elasticsearch/reference/current/transform-examples.html