As a technologist, I really value my research time
and often that I dedicate some specific time
to learn something new that I don't know.
And often it starts with a new acronym.
Hello, my name is Jamil Spain,
Brand Technical Specialist
with the US financial services market.
And our topic for today is
what is ETL?
Now the way I like to break this down is
first, define what this acronym means,
and then we'll discuss the benefits
and why it's so important to
actually implement into your architecture.
So we're going to start it off with
a little bit of cheer.
First, give me that E!
The E stands for "extract".
When you do ETL, you're going to be
bringing in data from a variety
of different data sources.
And the goal, once you have all of
them together, you're going to do
that T for "Transform".
Once that data is all together,
you do the process of decoupling,
de-normalizing, combining,
reshifting, data that you
never had the perspective to put
together before.
Now you have your own playground
to really start to make some new relationships.
Maybe you throw in a little bit of
relational database and SQL
in there to do some processing as well.
Finally, the last one?
Give me that L!
It stands for "load".
So after you have this new view,
new perspective on your data, you're
going to want to load that new
curated data into
another data source.
So now that we know what ETL means,
the next obvious question is
why is this so important?
And as technologists, we like to
invest our time into
things we know we're going to get
the value out of as well.
So but first, let's talk about
benefits over here that we're going
to see.
The next is the first one is going
to give you "Context". So
as you work with the data, you're
going to now have deep historical
data.
Based upon your specific
application.
Specifically, for your use case
that you'll have,
and with that will come a certain
"Consolidation" of
all your data that
you'll have, having all that data
in one place really
gives you the perfect ground
for analysis and reporting
and having it all available
to constantly update and still
be there for you.
Now, as I think about what ETL
accomplishes, think about what it
takes to do that manually.
You can probably guess what this "P"
is for and that is for
"Productivity".
OK.
At some point, you will probably
have to, if you did not have ETL,
you have to manually do all
this together, and so you're going
to come up with a repeatable
process.
You just keep feeding data in
and it comes out giving you the
context and also
giving you the perfect analysis
ready view for you to
use.
All right. And the last that you can
think of the A is
for "Accuracy".
So definitely as
you bill all this information,
you have the concept, the context
of your data is already
consolidated, is repeatable, you
keep feeding data in.
Now what I want to do my long
running reporting, I want to base
my nice fancy charts off this data.
Or maybe you want to get into
situations where you have auditing
or reporting standards that you must
provide this data.
You have all this information coming
from different sources, already
curated, constantly feeding in.
So.
When it comes, whether you're
starting your first data warehouse
project or your existing warehouse
or you're doing your application,
you're generating large amounts of
data. Consider ETL and
what it can do for you.
Thank you for your time.
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