FINAL WORD
infrastructure environment and historical
approach may have held you back from
implementing. Ok, I hear you say, I get the
theory but how do I turn this into practice?
Let me take a step back here for a second
to explain. . . .
Rob Mellor, VP GM EMEA, WhereScape
Quite simply, a combination of available
skills, investment and ingrained processes
mean that moving to the cloud overnight
may not be realistic, practical or even
desired. While a complete migration
to the cloud remains the end goal, an
ability to start smaller, pick a first project
to migrate and successfully work in a
hybrid environment for the time being is
crucial to continuing to meet the needs
of the business. And one key metric that
determines IT success in doing so is Time to
Value (TTV).
In today’s quarterly-driven world, the
time it takes to drive the return on any
strategic investment is critical. Put simply;
agile, responsive businesses outperform
slow-moving, reactive ones. Time to Value
(or TTV) is increasingly driving business
decisions as a result. And nowhere does
this need to be more closely scrutinised
than when investing in the technology that
contributes to making the right business
decisions; robust and efficient data analytics
capabilities that are essential for today’s
best businesses.
So, as you start your transition to the cloud,
how do you preserve and improve the all-
critical Time to Value at every step along
the way? You retool your processes to
take advantage of new technologies while
also leveraging agile data warehousing
best practices that your existing data
104
INTELLIGENTCIO
Around 20 years ago, when data
warehousing first became a ‘thing’, it was
heralded as the means to transform how
we do business. Data would be managed
efficiently, insights would flow and
businesses would benefit exponentially.
Except that the logistics of building and
managing a workable data warehouse were
way more complex than we first hoped. The
result? The power of data resided with a few
specialists, its extraction in any meaningful
form was slow and the resultant political
struggles actually slowed Time to Value
rather than accelerated it!
Even more frustratingly, on-premises data
warehouses were hugely expensive and
“
NOT ONLY
ARE IT TEAMS
DELIVERING
FASTER TIME
TO VALUE, THEY
ARE SEEING
STRONGER CODE
RELIABILITY AND
CONSISTENCY
THAT BETTER
POSITIONS IT
FOR INCREASED
RESPONSIVENESS
TO FUTURE
BUSINESS NEEDS.
inhibited agility. Building a data warehouse
took years and cost millions, meaning only
the richest companies could afford one.
Companies had to estimate how much
storage and compute power was needed
three years in advance and purchase
capacity for peak workloads (eg: end of
month processing, nightly ELT processing),
which would then sit underutilised or idle
for the bulk of the time frame. Buy too
little and you ran out of space and lost the
ability to do the job, buy too much and you
wasted huge amounts of money on unused
processing capacity.
The cloud has changed this dynamic by
allowing us to only pay for what we need.
Cloud-based infrastructure enables you
to do a special project for a few months
or maybe a proof-of-concept trial and
simply fire up the necessary capacity for
the duration of the project. Once it is
complete, you can instantly scale back
down. And when you don’t have to include
new hardware costs for a particular project
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