Time series data is of growing importance, especially withthe rapid expansion of the Internet of Things. This concise guide shows youeffective ways to collect, persist, and access large-scale time series data foranalysis. You’ll explore the theory behind time series databases and learnpractical methods for implementing them. Authors Ted Dunning and Ellen Friedmanprovide a detailed examination of open source tools such as OpenTSDB and newmodifications that greatly speed up data ingestion.
You’ll learn:
A variety of time series use cases
The advantages of NoSQL databases for large-scale time series data
NoSQL table design for high-performance time series databases
The benefits and limitations of OpenTSDB
How to access data in OpenTSDB using R, Go, and Ruby
How time series databases contribute to practical machine learning projects
How to handle the added complexity of geo-temporal data
For advice on analyzing time series data, check out Practical Machine Learning: A New Look at Anomaly Detection, also from TedDunning and Ellen Friedman.
