If you’ve heard of what a ‘Mega Trend’ is in tech, you’ll know that a ‘Mega Trend’ comprises of something with such impact that it will have an effect across business, economy, society and people’s personal lives in a profound way.
On that same note, if you have heard of Big Data you’ve very likely heard of cloud computing too, however with the oncoming rise of, IoT (Internet of Things) devices, AI (Artificial Intelligence) and machine learning, as well as the continued exponential growth of mobile and social, the two are becoming more and more reliant on one another.
Flip back ten years ago and you would have needed a fairly specific engineer or data analytics team to dive into a big data cluster and maybe get some solid actionable results out the other end.
In its infancy, big data was generally difficult to manage. Even now the systems weren’t the most straightforward and the parameters of it were frequently changing.
The challenges faced when trying to corral big data into submission are shared by all. As businesses look at tackling monumental blobs of data to gain amazing insights and truly refine processes.
With the launch of Hadoop in 2006, many companies found their answer in the Apache-based software that offered a framework for distributed storage and data processing. In turn, this has laid the groundwork for a new star child in 2017... big data in the cloud.
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The fortunate thing with mega trends is that the rate in which their popularity see’s them mature can vary.
Cloud computing has matured at a much faster rate than big data, which luckily for us has allowed cloud to solve many of the issues that made big data such a complicated area to dive into.
A common challenge for so many with cloud computing is the legacy issues that arise from infrastructure migration and compliance mitigation, so big data shares several of the same inherent problems.
With cloud services, one of the overwhelming Unique Selling Points (USP) for avoiding the challenges above is the benefit of an externally hosted infrastructure... and the fully managed services that come along with it.
Businesses have grown to focus highly on multi-cloud strategy, the effective use and deployment of hybrid infrastructure and operational systems such as DevOps culture.
It’s no surprise that the big players in cloud computing have now come up with offerings such as Google BigQuery, Amazon Redshift, and Microsoft Azure HDinsight to unify your cloud and big data infrastructures.
By removing half the issues stopping businesses from committing to fully fledged big data usage, the emergence of managed Hadoop (and even managed spark) via the cloud allows for the simplicity of pay as you go cloud used for big data. Just upload your data set and start processing without all the fuss.
Just as with the evolution of cloud, big data has improved its ease of use. It’s finally taking shape as a relatively fluid resource with many dynamic applications across a huge amount of industries.
With IoT, AI and machine learning all fast approaching mainstream adoption, so is a monumental amount of data.
Highly skilled staff, data analytics firms and specialist businesses in areas such as social listening, built around data analysts, no longer form a boundary to accessing and using big data’s secrets for any business.
As the cloud grows–actively promoting price efficient models, pay as you go schemes, code and forget deployment systems–so does big data.
The general take away is that provisioning big data clusters used to be nothing short of complicated and almost always a burden for IT departments. Where as now, with a plethora of choices of how to tackle it made possible via the cloud, it’s easy.
Now let every other department wow you with the revelations they make with Big data in the cloud. Sit back, and let the insights start rolling in.
Does this sound like you or your business? Whichever way your data is coming in, and whatever way you’re trying to process it, we at Cloudhelix promise you, we can make it easier, just give us a call or an email on the links below.
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Posted in Managed Cloud on Jul 03, 2017