But this situation is changing,
as some companies have recently
introduced data analytic software
specifically designed for creating
insights and extracting value from
the time-series data stored in
historians such as OSIsoft PI. These
companies are not only making it
easier to rapidly enable investigation
of historical data, but they are also
taking a more modern approach
to the software delivery and user
Different data analytic software
products have varying deployment
models and features, but most follow
these basic steps:
1. On deployment, the data
analytics software connects to
the historian. Most historians
reside on the corporate intranet, so it’s
easy to make this connection by installing
the software on a workstation or server
connected to the intranet. The software
then automatically locates the historian and
establishes the connection.
2. Automatic indexing of the tag or sensor names
in the historian to make them easy to search
and access the related data. This step typically
takes less than an hour for tag counts of up to
250,000 tags, and occurs just once at setup.
Once this step is complete, live data from the
historian is available in the software for the
user to investigate and analyze.
3. The user searches the historian and other data
sources for the data points of interest. This
is typically done using a Google-like search
algorithm. Search terms correspond to data
names given in the historian, and any part
of the name can be used in the search. For
example, a dryer temperature could be found
by searching on its tag name, TT-101, or its
label, Dryer Inlet Temperature, or a subset of
the name string.
4. Users can then visualize the time series data
over a designated period time. This feature has
long been associated with trending packages,
but new search tools using visual patterns,
limits and the ability to dimensionalize data
with context from other data sources improves
the trending experience.
5. Finally, just as the trend viewer experience
is redefined by this next generation of data
analytics software, so too is the user experience.
Work can be stored for reuse or shared
with colleagues, either as a way to capture
expertise, or in real-time to enable distributed
discussions across an organization. And, of
course, the deployment model for the software
accommodates customer requirements for
on-premise, cloud, or hybrid scenarios.
DISCOVER BETTER DESIGNS. FASTER.
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VIBRO-ACOUSTICS − MULTIDISCIPLINARY DESIGN EXPLORATION