Book Image

Time Series Analysis on AWS

By : Michaël Hoarau
Book Image

Time Series Analysis on AWS

By: Michaël Hoarau

Overview of this book

Being a business analyst and data scientist, you have to use many algorithms and approaches to prepare, process, and build ML-based applications by leveraging time series data, but you face common problems, such as not knowing which algorithm to choose or how to combine and interpret them. Amazon Web Services (AWS) provides numerous services to help you build applications fueled by artificial intelligence (AI) capabilities. This book helps you get to grips with three AWS AI/ML-managed services to enable you to deliver your desired business outcomes. The book begins with Amazon Forecast, where you’ll discover how to use time series forecasting, leveraging sophisticated statistical and machine learning algorithms to deliver business outcomes accurately. You’ll then learn to use Amazon Lookout for Equipment to build multivariate time series anomaly detection models geared toward industrial equipment and understand how it provides valuable insights to reinforce teams focused on predictive maintenance and predictive quality use cases. In the last chapters, you’ll explore Amazon Lookout for Metrics, and automatically detect and diagnose outliers in your business and operational data. By the end of this AWS book, you’ll have understood how to use the three AWS AI services effectively to perform time series analysis.
Table of Contents (20 chapters)
1
Section 1: Analyzing Time Series and Delivering Highly Accurate Forecasts with Amazon Forecast
9
Section 2: Detecting Abnormal Behavior in Multivariate Time Series with Amazon Lookout for Equipment
15
Section 3: Detecting Anomalies in Business Metrics with Amazon Lookout for Metrics

Preparing a dataset for anomaly detection purposes

Throughout this chapter and the next one, we are going to focus on an e-commerce dataset in which we will detect potential anomalies and identify some root causes to help us investigate the problems and deliver a faster route to remediation.

In the sub-sections that follow, we are going to look at the following steps in detail:

  1. Download the e-commerce dataset and split your data into a training dataset (that you will use for backtesting purposes) and a testing dataset (that you will use to monitor simulated live data to understand how the continuous mode of Amazon Lookout for Metrics works).
  2. Upload your prepared CSV files to Amazon Simple Store Service (S3) for storage. Amazon S3 lets you store files and is often used as a file datastore for many AWS services such as Amazon Lookout for Metrics.
  3. Authorize Amazon Lookout for Metrics to access your data in Amazon S3. This is optional as you can let Amazon Lookout for...