FEATURE: BIG DATA
gap that exists. Complicating matters is the
dynamic and continually changing nature
of data and its associated requirements.
But there are positive signs. Recognising
the importance of data in the country,
universities are introducing degrees in Big
Data science.
For its part, those businesses invested in
data analysis and the related solutions and
technologies should also work with tertiary
institutions in providing the expertise
required to assist with the curriculum. Data
is not going to go away. Modern enterprises
need to evolve from policy-based to
behaviour-based data management and
is going to require even more data-savvy
specialists to move to the next level.
GRANT BENNETT, COUNTRY
Grant
Bennett, Country
Manager:
South &
MANAGER:
SOUTH
AFRICAN
African
& Sub-Saharan Africa,
SUSE SUSE
SUB-SAHARAN
AFRICA,
Data growth is not like economic growth or
growth on savings in a bank – a sluggish few
percentage points grudgingly added over long
periods – it’s incredibly rapid, long into double
figures and the interest rate is compound.
In fact, many have described this growth as
explosive – which, if not managed correctly
has the connotations of damage.
For instance, while storage costs might have
come down a lot over the last few years,
those savings are more than negated by the
volume growth rate, creating major issues
for many, as reduced capital spending has
become the norm.
As a result, though businesses are still looking
at ways to ‘do more with less’, we have
reached the limits of ‘if it isn’t broken, don’t
fix it’ – yet everyone knows things have to
change. But how? Well some things are
crystal clear when we look at the growth of
Big Data:
1. Outside of the ‘hyperscalers’ hardly
anyone will be able to afford to own
and host all their compute power on
premise. In the future, a proportion of your
compute power is going to be in public
clouds, one way or another, sooner or later.
2. Storage growth is massive and
unsustainable. You are going to need to
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find a better, cheaper way of doing it,
and that way is going to need to work in
harmony with your compute decisions.
3. Vendor lock-in is never a good idea. In
a world where business models change,
discovering you’re locked into a cloud
provider might be one of the most
unpleasant discoveries of your life.
Analysing Big Data presents huge
opportunities for innovation and growth,
but big challenges as well. Businesses today
need high performance computing solutions
to solve data intensive problems and keep
pace with growing processing needs.
What’s more, because of the clouds’ on-
demand model, many enterprises see it as a
cost-effective way to access the multitude of
computing resources required for processing
Big Data. This is also where software-defined
storage (SDS) comes in – especially if we
consider that by 2020, between 70 and 80%
of unstructured data will be held on lower-
cost storage managed by SDS environments.
Businesses are moving too fast and creating
enormous amounts of data to rely on
storage architectures that are proprietary,
overpriced and inflexible.
At the same time, IT is also challenged
with organising storage assets as a bridge
between new and old, with the same level
of performance across locations and classes.
Truly unlimited scalability enables enterprise
IT organisations to deliver the agility
businesses demand by non-disruptively
adding capacity at the cost they want to
pay. This in turn allows organisations to
spend more time focused on analysing
and utilising the data to deliver future
Kate Mollett, Regional Manager for Africa
South at Veeam
innovations to the business, rather than
worrying about storage. The shift toward
SDS is also largely driven by a substantial
cost reduction without compromising a
previously commoditised technology.
With future storage demands growing
exponentially to account for Big Data,
having technology that’s handled as an
operating expense can also lead to a huge
cost reduction.
Big Data is now on the doorstep of
organisations across all sectors. To get
maximum value, businesses need to be
able to rapidly process huge sets of varied
data in a cost-effective way but to do that,
they need the right foundation to overcome
barriers and capitalise on the valuable data
that exits in the organisation. n
BUSINESSES TODAY NEED HIGH
PERFORMANCE COMPUTING
SOLUTIONS TO SOLVE DATA INTENSIVE
PROBLEMS AND KEEP PACE WITH
GROWING PROCESSING NEEDS.
www.intelligentcio.com