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

Adding a dataset and connecting a data source

We are going to ingest our data into Amazon Lookout for Metrics to start detecting anomalies in it. To do this, complete the following steps:

  1. On the detector dashboard, click on the Add a dataset button.
  2. In the Basic information section, just give a name to your dataset (I called mine ecommerce-dataset).

Figure 14.15 – Dataset basic information

  1. In the Datasource details section, we are going to start the backtest mode to find anomalies in historical data. To do this, select Amazon S3 in the Datasource dropdown and then select Backtest for Detector mode.

Figure 14.16 – Datasource details – Backtest mode selection

  1. Then, you will point Amazon Lookout for Metrics to your input dataset where you have your historical data. If you followed the dataset upload section earlier in this chapter, the S3 path to your historical data will have the following...