Chapter 9: Creating a Dataset and Ingesting Your Data
In the previous chapter, you learned about anomaly detection problems and some ways to tackle them. You also had an overview of Amazon Lookout for Equipment, an AI-/ML-managed service designed to build anomaly detection problems in multivariate, industrial time series data.
The goal of this chapter is to teach you how to create and organize multivariate datasets, how to create a JSON schema to prepare the dataset ingestion, and how to trigger a data ingestion job pointing to the S3 bucket where your raw data is stored.
In addition, you will also have a high-level understanding of all the heavy lifting the service is performing on your behalf to save as much data preparation effort as possible (imputation, time series alignment, resampling). You will also understand what kind of errors can be raised by the service and how to work around them.
In this chapter, we're going to cover the following main topics:
- Preparing...