Using Elasticsearch and Kibana

Using Elasticsearch and Kibana

Elasticsearch wears two hats: It is both a powerful search engine built atop Apache Lucene, as well as a serious data warehousing/BI technology.

This course will help you use the power of ES in both contexts

ES as search engine technology:

• How search works, and the role that inverted indices and relevance scoring play
• The tf-idf algorithm and the intuition behind term frequency, inverse document frequency and field length
• Horizontal scaling using sharding and replication
• Powerful querying functionality including a query-DSL
• Using REST APIs - from browser as well as from cURL

ES as data warehouse/OLAP technology:

• Kibana for exploring data and finding insights
• Support for CRUD operations - Create, Retrieve, Update and Delete
• Aggregations - metrics, bucketing and nested aggs
• Python client usage

Scalable Search and Analytics for Document Data

Url: View Details

What you will learn

• Construct robust, scalable search for production use in web and enterprise apps
• Query ES using the ES Domain Specific Language
• Perform aggregations to extract insights and run analytics on ES

Rating: 4.15

Level: All Levels

Duration: 6 hours

Instructor: Loony Corn