Database Reference
In-Depth Information
aggregation you choose here isn't important—we'll suggest
AVG(corpus_date)
, but you could just as easily use
MIN
or
MAX
because
all the values for a single corpus will be identical.
The date dimension, however, is going to be skewed by the corpora that you
saw earlier that don't have publication dates:
various
and
sonnets
don't
have a single date, so they're recorded as 0. You can see this immediately
because it skews the coloring so that you can't see the difference in
gradations between the other plays. To fix the skew, you can change the
scaling. Right-click
AVG(corpus_date)
, choose Edit Colors, then click
Advanced. In the Advanced menu, you can set a custom range; set it to
start at 1590 and end at 1620, which is the range of Shakespeare's writing
career. After you make this adjustment, you should see lighter bars for the
earlier plays, such as
King Henry VI
, and darker ones for the later ones, such
as
The Tempest
.
Figure 13.6
shows this graph; see if you can tell whether
Shakespeare got longer-winded as he got older.
Visualizing Your BigQuery Data with BIME
Do you find it a little bit odd that to visualize your data in the cloud, you have
to install software on a Windows desktop machine to access your data? After
all, your data lives in the cloud, so why can't you access it via the cloud?
For the cloud-o-philes, BIME Analytics offers a robust cloud-based data
visualization option that works from any flash-enabled web browser. This
enables you to analyze your data that lives in the cloud while keeping it in
the cloud. BIME can connect to dozens of different types of data sources,
including BigQuery, and visualize them live. It also offers an option to pull
your data out of whatever datastore it is currently in and store it in a
BigQuery dataset. It provides a variety of extract, transform, and load (ETL)
options to help finesse your data into a format that makes it easy to query.
We won't go into the ETL option further, but using BIME to automatically
import your data into BigQuery can be a great way to save you the overhead
of managing it yourself.
BIME may be cloud-based, but it is not free. You should consult the pricing
determine whether it is within your budget. BigQuery is only available in
the Big Data pricing tier, which might seem cheap if you're running a large
enterprise, but it might seem expensive if you just have a couple of tables
