This course is a hands-on guide to using Elasticsearch used in conjunction with Elastic Stack, to ship, parse, store, and analyze data.
You’ll start this course by getting an understanding of what Elasticsearch is, what it’s used for, and why it’s important. Then you’ll be introduced to the new features in Elasticsearch 6. We’ll cover each of the fundamental components such as indices, documents, nodes and clusters, all which form the dichotomy of Elasticsearch. You’ll find out how to add more power to your searches using filters, ranges, and more. You’ll also see how Elasticsearch can be used with the other components of the Elastic Stack such as LogStash, Kibana, and Beats, to get data into an Elasticsearch cluster.
As well as learning how to add more power to your searches with filters, ranges, and more, you'll also see how to run advanced queries and aggregations on Elasticsearch 6. We’ll also implement Machine Learning in a step-by-step walk-through example of anomaly detection. We conclude by developing a quick working Elasticsearch application. By the end of this course, you’ll have a firm understanding of all the fundamentals of Elasticsearch 6, along with sufficient knowledge to use it in the real world.
If your aim is to dive into the world of data analytics, Elasticsearch is the excellent jump-off point. More specifically, this course is designed for technical professionals who aim to build efficient search and analytics applications using Elasticsearch 6. This video is for developers who look to make the jump from Lucene or Solr to Elasticsearch, as well as those with no prior experience in working with search and analytics technologies.