Database Reference
In-Depth Information
The Questions to Be Asked
The time series data use cases described in this chapter just touch on a few key areas in
which time series databases are important solutions. The best description of where time
series data is of use is
practically everywhere measurements are made
. Thanks to new tech-
nologies to store and access large-scale time series data in a cost-effective way, time series
data is becoming ubiquitous. The volume of data from use cases in which time series data
has traditionally been important is expanding, and as people learn about the new tools avail-
able to handle data at scale, they are also considering the value of collecting data as a func-
tion of time in new situations as well.
With these changes in mind, it's helpful to step back and look in a more general way at some
of the types of questions being addressed effectively by time series data. Here's a short list of
some of the categories:
1. What are the short- and long-term trends for some measurement or ensemble of meas-
urements? (prognostication)
2. How do several measurements correlate over a period of time? (introspection)
3. How do I build a machine-learning model based on the temporal behavior of many
measurements correlated to externally known facts? (prediction)
4. Have similar patterns of measurements preceded similar events? (introspection)
5. What measurements might indicate the cause of some event, such as a failure? (dia-
gnosis)
Now that you have an idea of some of the ways in which people are using large-scale time
series data, we will turn to the details of how best to store and access it.
