Cloud migration is now the most preferred option being used by enterprises
worldwide.
With the advent of digital transformation and increasing customers for online services,
migration from on-premise processing to the cloud has gained momentum. All know that cloud
infrastructure is advanced, sophisticated, and available on demand, making the technology
viable and affordable. Hence moving big data analytics to the cloud is only an expected
outcome of total digital
transformation.
Hesitation in Shifting from On-Premise to Cloud
Though migration to the cloud and adapting to the concept of ‘as a service’ is being adopted
by enterprises for the deployment of an application, there has been a certain hesitation
inmoving data for analytics to the cloud. ‘Why fix when nothing is broken’ is the basis of
the initial reluctance, and having data on-premise is still considered more secure. Of
course, it is generally accepted that the cloud offers scalability and performance
advantages for big data analytics, but privacy and cyber security are nagging afterthoughts
for any migration.
The First Step Is the Toughest
Cloud vendors have realized that moving big data to the cloud should be a step-by-step or
baby-steps approach. Initially, micro-projects involving small chunks of data should be
migrated to the cloud, so the customer gets an actual feel of cloud-based data analytics.
The experience of having a successful migration and seeing the actual advantages results in
changing the perception in favor of big data in the cloud. The first step is the toughest,
but soon enterprises start expanding their data analytics operations to the cloud and away
from legacy on-premise systems. The benefits of speed, reliability, and scalability are
appreciated though concerns of privacy, availability and data security need to be addressed
in a systematic and performance-based manner.
The Customer Begins to See the Advantages
After the trial run of using the cloud for big data analytics, most customers begin to fathom
the distinct advantages of using the cloud. Even though the comfort zone still exists for
on-premise infrastructure, the possibilities that open up via cloud migration are an
attractive proposition.
Scalability is one of the dominant factors driving customers to the cloud for data analytics.
Scalability is crucial for big data projects, but the clincher is that scalability
requirements can be requested and met on demand. So the pressure of projecting accurate
scalability is tremendously reduced as infrastructure expansion and upgrades are all
available at a request away.
Customers also love the idea that downgrades of infrastructure and services are also
available depending on project or company demands. Scale up or scale down – all easy
operations for the customer. This kind of flexible scalability is not feasible with
on-premise operations.
Everything is ‘as a service’ in the cloud. This flexible and on-demand availability of IT
infrastructure and services is a highly viable and favorable option for customers. Varying
business demands, budgets, financial restraints, and other corporate shackles that could
impede data analytics projects are now reduced. The ‘order-and-use service model’ for big
data analytics projects becomes a very attractive option over on-premise considerations.
Besides, sophisticated features, software, and infrastructure offered by cloud vendors are
numerous, and having access to such an array of technology would not be possible with
on-premise operations. This vast array of infrastructure, platforms, software, tools, and
services available on demand with the scalability as required is a huge plus point over
on-premise operations. It would not be affordable nor practical for a customer to acquire
on-premise all that the cloud has to offer for a data analytics project literally on ‘click
and request.’
The IT teams of customers would naturally choose the cloud option over the on-premise option
since everything is already set up and deployed for large data analytics projects. The team
can hit the ground running with this model for analytics projects. The convenient part is
that, when not required, all IT infrastructure acquired could be switched off and given back
at no additional and recurring costs.
Migration and Direction of Data Analytics
The highest use of data analytics is for predictive analytics, business intelligence, and
reporting capabilities across numerous sectors such as healthcare and the public sector.
There has been an exponential increase in data mining to be done due to the huge increase of
users and available services. Keeping up with this explosion requires all analytics projects
to ramp up with networking technologies, tools, processing power, and storage.
This kind of upgrade is now most feasible with the cloud as on-premise would be expensive,
slow to turn around, and inefficient. The introduction of artificial intelligence and
machine learning into data analytics architecture has further complicated matters in terms
of demand for processing power, technology tools, and other IT infrastructure. The customers
are convinced that these demands for advanced data analytics can only be met via migration
to the cloud.
Big data analytics for social media analysis is on the increase as well. Social media data is
huge and constantly on the increase. Mining this data, along with all the analysis required
and mixed with artificial intelligence and machine learning, makes the cloud the clear
platform winner for the way forward for data analytics.
Bottom Line – A Mix of Many Technical Worlds and Expertise Is Needed
The way forward for any data analytics project is a mix of many worlds, all converging on
data. Kyyba excels at Data transformation, End to End Data testing covering a traditional
database or data warehouse or data lakes, orchestrating data pipelines to move large volumes
of data from different sources to a target destination, Setting up & running training
& deployment environments for AI/ML Models and cloud migration are now linked to an
intricate web of sophisticated technologies.
All these capabilities take advantage of the cloud to process large volumes of data, which
is reliable, trustable, and durable to offer that report or dashboard to your customers
which shows accurate results that power their business. Get in touch to
learn more.
