Databases Reference
In-Depth Information
group always like to thumb things down, and some third group of
users are a mix. What's the definition of a “mix”?
Now that we've started to get some sense of variation across users, we
can think about how we might want to
aggregate
users. We might make
the x-axis refer to time, and the y-axis refer to counts, as shown in
Figure 6-4
.
Figure 6-4. Aggregating user actions into counts
We're no longer working with 100 individual users, but we're still
making choices, and those choices will impact our perception and
understanding of the dataset.
For example, are we counting the number of unique users or the overall
number of user logins? Because some users log in multiple times, this
can have a huge impact. Are we counting the number of actions or the
number of users who did a given action at least once during the given
time segment?
What is our time horizon? Are we counting per second, minute, hour,
8-hour segments, day, or week? Why did we choose that? Is the signal
overwhelmed by seasonality, or are we searching
for
seasonality?
