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What's on Your Favorite Data Manager's
Christmas List?
I'm
willing to bet there are certain things that just
about all data managers would like to find in
their stockings. The question is, can Santa influence
business users? And vendors?
See
my article Dear
Santa, I've been a good data management manager
on SearchDataManagement
(free registration required) and be sure to add
your own wish list items in the comments section
at the end.
*
Like
asking for directions, accepting that we need
training is a leap for some of us. This month's
article dispels the notion that training is superfluous.
Enjoy it, and let
me know what you think.
 Training?
We don't need no stinkin' training ...
by
Rick
Sherman, Athena IT Solutions
While
data warehousing technologies and methodologies
have evolved over the years, ideologies, in many
cases, have not. Taking a narrow-minded approach
to your data warehousing strategy can be like
trying to drive with your parking brake on.
One
of the biggest mistakes project teams make is
in refusing to acknowledge the need for training.
This is just one of the ways companies undermine
their own efforts to take data warehousing to
its full potential.
When
faced with an unfamiliar task we generally use
our previous experience as a point of reference
to determine how we should react. Likewise, when
people built their first data warehouse, they
often modeled it after their familiar transaction
processing systems. They built what they knew
and were comfortable with instead of using the
new paradigm offered by data warehousing.
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“When people built their first data
warehouse, they often modeled it after their
familiar transaction processing systems. They
built what they knew and were comfortable
with instead of using the new paradigm offered
by data warehousing. ” |
As
a result, the first generation of data warehouses
often shared many data modeling and architectural
characteristics with their data source systems.
This tendency to use outmoded yet familiar techniques
was exacerbated in the 1990's. At that time, there
was such a rush to build IT systems that people
often did not have time to learn new techniques
and approaches. But the downside of building something
in "Internet time" meant doing it fast
and taking shortcuts. Each initiative —
ERP, CRM, supply chain, data warehousing and many
others — had marching orders to produce
and to produce fast. There was not much time to
learn new and more suitable approaches.
Compounding
the problem was that with so many IT systems being
built, there was a strain on the IT workforce.
There were not enough experienced people for projects;
many were stretched too thin. In order to obtain
the appropriate resources, many companies relied
on consultancies to build their IT systems. However,
consulting firms were experiencing growing pains
of their own, and had trouble hiring enough IT
experts. In addition, many consultants, themselves,
were struggling to get acquainted with data warehousing.
Demanding timetables left little time to be trained
in the new approaches.
So,
many data warehouses were not really built in
the new data warehousing paradigm, which focuses
on storing and setting up data for consumption.
No one knew any better – not IT, business
groups, consultants, or even some industry analysts.
They, too, were struggling to "learn on the
fly." And unfortunately, although many of
these data warehouses were incorrectly designed,
they continue to grow and expand. In fact, the
very people who built them incorrectly are now
"experts" who continue to build new
data warehouses using bad techniques that focus
on transmitting data. Without comprehensive data
warehousing education, the first generation
mistakes are being repeated in succeeding generations.
Getting
the right kind of training is important. Technical,
i.e. software product training, is not enough.
Often, software vendors offer courses in addition
to their product-specific training, or devote
a portion of a class on BI or ETL tools to data
warehousing concepts. Although this is useful,
it is generally not detailed enough to really
give people an understanding of what is involved
in developing a data warehouse. And although the
people teaching vendor-sponsored classes are quite
knowledgeable in their tools, they may not have
many years of data warehousing experience to draw
upon in their teaching.
It's
best to seek out data warehousing training that
reviews concepts, architectures and best practices.
This training should involve discussing data integration
and data modeling, because that is the crux of
the new data warehousing paradigm. There are also
some very fine books that can teach you this information.
But get books that have chapters on architecture,
data integration and data modeling. Here are a
couple of Ralph Kimball books I suggest:
So
how do you justify getting data warehousing training
or "expensing" data warehousing books,
especially if you have been involved in your company's
data warehouse program? Pitch your training as
necessary to support your company's performance
management program, regulatory initiative (such
as Sarbanes-Oxley) or effort to provide real-time
data to the business. Your investment of time
and expense in really understanding data warehousing
will be abundantly rewarded when you improve your
company's CPM, BI or DW initiatives in the future.
For
more information on BI and DW training, see our
course descriptions and schedule on our data
warehouse training page.
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