AWS Certified Data Analytics Specialty 2021 - Hands-On! - Introduction to Amazon Elasticsearch

The video tutorial explores Elasticsearch, a powerful tool for large-scale data analysis and reporting. Initially a search engine, Elasticsearch has evolved into a comprehensive analysis and visualization tool, part of the Elastic Stack. It is built on Lucene and is highly scalable, supporting petabyte-scale datasets. The tutorial covers components like Kibana for visualization and Logstash for data streaming. Elasticsearch is used in various applications, including log analytics, security analytics, and clickstream analytics. Key concepts include documents, indices, and shards, emphasizing its scalability and efficiency.

What was the original purpose of Elasticsearch?

• Data storage

• Machine learning

• Search engine

• Data visualization

Which component of the Elastic Stack is used for data visualization?

• Logstash

• Elasticsearch

• Kibana

• Beats

What is one of the primary uses of Elasticsearch today?

• Building mobile apps

• Image processing

• Log analytics

• Video streaming

Which company uses Elasticsearch for application monitoring and root cause analysis?

• Adobe

• Expedia

• Hearst Corporation

• Amazon

What is a document in the context of Elasticsearch?

• A type of database

• A unit of data storage

• A visualization tool

• A data processing framework

How does Elasticsearch achieve horizontal scalability?

• By distributing data across multiple nodes

• Through vertical scaling

• By reducing data size

• By using a single server

What is the role of shards in Elasticsearch?

• To store metadata

• To manage user access

• To divide data for scalability

• To visualize data