Execute Analytics Queries in Couchbase

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.
Course info
Level
Advanced
Updated
Mar 24, 2020
Duration
2h 5m
Table of contents
Description
Course info
Level
Advanced
Updated
Mar 24, 2020
Duration
2h 5m
Description

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
About the author

An engineer at heart, I am drawn to any interesting technical topic. Big Data, ML and Cloud are presently my topics of interest.

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Section Introduction Transcripts
Section Introduction Transcripts

Course Overview
[Autogenerated] Hi and welcome to this course. Execute Analytics queries in Touch Base. My name is Keisha Year on I will be your instructor for this course a little about myself First, I have a master's degree in computer science from Columbia University on her previously worked in companies such as DeutscheBank on Web MD. In New York. I presently work for lunatic on a studio for high quality video content as it gets easier and easier to gather data performing analytics operations to understand what it conveys and then make the right business decisions is becoming more and more important. Which is why out base influence on analytic service to simplify the start off data analysis. And if course we delve into the implementation off analytics as a separate service in Couch base so that it does not interfere with operations on bucket data, we explored the steps needed the set of 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 Couch with Analytics, which is known as a nickel for analytics. We look at how this is similar to yet certainly different from regular nickel on look into various operations, which can be performed with this language. The explore A number of clauses which are analytic squares, can include the operators which we can use, as well as the buildin functions, which can be invoked to operate on document dater. Finally recover the youth off window functions from analytics operations over partitions of data. Once you have finished, of course, you will be well equipped to make sense off large volumes off document data using the Couch based analytics service. This will help you spot trends in the underlying information prepared. The data for visualizations on ultimately will help your organization make the right business decisions based on an analytical and data driven approach.