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In this specialization, you will learn Elasticsearch’s role in the Elastic Stack and how to install, configure, and manage it for data search and analytics. You’ll discover how Elasticsearch powers search engines and analytics and gain proficiency in interacting with it through APIs, creating indices, and managing data.
The first section covers Elasticsearch installation and basic concepts like term frequency, indices, and documents. You’ll also learn HTTP and RESTful APIs for interacting with Elasticsearch, and apply these skills through exercises like indexing movie data.
As you progress, you’ll explore scaling Elasticsearch, optimizing queries, and using Kibana for data visualization. You’ll also learn to handle large datasets, perform log analysis, and manage Elasticsearch in the cloud.
Designed for learners in data science, software development, and cloud technologies, this specialization is perfect for those looking to work with big data and enhance search engine capabilities.
By the end of the specialization, you’ll be able to install, configure, and manage Elasticsearch clusters, scale data, and integrate with tools like Logstash, Kibana, and Kafka for cloud-based deployments.
Praktisches Lernprojekt
Learners will build projects focused on real-world data management and search challenges, using Elasticsearch and related tools like Logstash and Kibana. They will apply skills in mapping, indexing, and searching data, working with the MovieLens dataset to practice importing, updating, and managing data. In later exercises, learners will integrate Elasticsearch with external data sources such as Kafka and Apache Spark to handle large datasets. Finally, they will create data visualizations in Kibana, enhancing their ability to analyze and interpret complex datasets, and driving actionable insights. These projects help solve authentic problems in data integration and visualization.
