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Execute Analytics Queries in Couchbase 6

by Kishan Iyer

This course covers the use of the Analytics service in Couchbase and the use of its query language - N1QL for Analytics. It includes use cases, the architecture which supports analytics, and the execution of queries to understand the underlying data.

What you'll learn

As it gets easier and easier to gather data, performing analytics operations to understand what it conveys and make the right business decisions is becoming more and more important. Which is why Couchbase includes an analytics service to simplify the task of data analysis.

In this course, we delve into the implementation of analytics as a separate service in Couchbase so that it does not interfere with operations on bucket data. We explore the steps needed to set up data so that they can be used by analytics, and then focus on running analytics queries.

We then turn our attention towards the query language for Couchbase analytics which is known as N1QL for Analytics. We look at how this is similar to, yet subtly different from regular N1QL and look into various operations which can be performed with this language.

We explore a number of clauses which our analytics queries can include, the operators which we can make use of as well as the built-in functions which can be invoked to operate on document data.

Finally, we cover the use of window functions to perform analytics operations over partitions of data.

Once you have finished this course, you will be well equipped to make sense of large volumes of document data using the Couchbase analytics service. This will help you spot trends in the underlying data, prepare the data for visualizations, and ultimately will help your organization make the right business decisions based on an analytical and data-driven approach.

About the author

I have a Masters in Computer Science from Columbia University and have worked previously as a developer and DevOps engineer. I now work at Loonycorn which is a studio for high-quality video content. My interests lie in the broad categories of Big Data, ML and Cloud.

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