NC Feb-Mar 2023

FEATURE: DATA PERSPECTIVES
petabytes of data globally within an
enterprise and for most, the challenge can
seem daunting. Successful enterprises can
navigate through these requirements,
however - but it can be costly.
Businesses in regulated industries must
prove that they can effectively store a
certain type of sensitive data, but also
must be able to prove that, when
permitted, this data no longer exists
anywhere. If this data has been deleted,
but still shows up in any form or location,
the data can still be recalled, which can
bring on litigation cases against the
business. It does not matter whether the
enterprise is aware of the existence of the
rogue data or not, they are still liable. The
Data Life Cycle Management process is
the sequence of the creation, use,
retention, and eventual erasure of data. In
some industries, the duration of this life
cycle can span decades or more.
The associated costs and burden which
businesses have of managing data,
tracking its movements, replication, and
its locations, can place a massive strain
on the ability of an organisation to
conduct the business they need to do. The
issue is the "use" phase of the data's life
cycle - how do businesses make data
useful, accessible, and analysable across
a vast web of multinational regulations,
without losing track of it? The answer is
perhaps simpler than expected - leave the
data in place, where it is safe and
controllable - leave the original as the
original.
Even though analysing data-in-place
sounds like an easy solution to this
industry problem, it is not the first time this
approach has been tried. The problem of
network latency comes into play - it is not
sufficient to just access the original data
where it persists from anywhere. The race
between network latency and data size
has been a back-and-forth struggle
throughout the history of computer
networking. Even as the world gets
digitally smaller, network latencies can
make accessing data seem too far away
to be efficiently analysed with high
performance analytical databases engines
which are already on the market.
WHAT IS THE SOLUTION TO
NETWORK LATENCY?
There are three primary types of network
latency which are; latency caused by
distance, latency caused by congestion,
and latency caused by the network design
itself, intentionally or by accident.
Combinations of these latency types in the
same network, makes the issue much
worse. All three types can, however, cause
analytic access to data to be too slow to
be useful, which reduces the usable
throughput, which is required to gain
insight from critical data, to outright
intolerable.
The instinctive solution is to place the
data near the processing engines, where it
is needed. This means copying data to
local storage locations to give the data
local performance access. However, this
creates a whole new set of issues.
Needing to keep track of where all of
these data copies are located and when
the use of the data is completed and
removing the data from all locations, can
be difficult and costly. This includes
tracking down potential locally backed up
copies and any off-site media copies, and
local disaster recovery replicas in those
remote locations.
The simplest and most practical
solution is to leave the original data in
place. This is possible today with the
combination of technologies
which are already on the
market. When businesses
choose the right
combination, they could optimise
latencies in Wide Area Networks (WAN)
and potentially increase throughput by
over seven-times when directly compared
to the same WAN by itself.
Businesses could be able to use as much
as 95 percent of the WAN connection to
analyse data where it is stored versus
copying and staging the data closer to
their analytic engines. That is global
analytics with data-in-place and at scale.
This frees up IT teams to solve bigger
issues, rather than needing to keep track
of where sensitive data is being copied.
They can manage and control data where
they need to. This also has the potential
to minimise regulatory requirements as
some regulations allow the transient
inflight use of data versus the persistence
of data in other countries.
The cost savings and reduced
management spent could also play a role
in planning data access methods.
Combining the right technology is perfect
for on-premises, private, hybrid, public
and multi-cloud environments where long
network latency might halt enterprises
from being able to fully leverage access to
their sensitive data. NC
WWW.NETWORKCOMPUTING.CO.UK @NCMagAndAwards FEBRUARY/MARCH 2023 NETWORKcomputing 27