Time to rethink big data

What size do things start?

Big data and analytics is the next big thing, so why has it yet to register in mainstream adoption?

Perhaps one reason is that it’s frequently described in ways that suggest it’s inaccessible to all but the largest enterprises. The picture the market has painted is that of behemoth computing engines crunching astrological sized datasets with teams of developers to make it do what they need for the business. And while this is true in pockets of the market, what about the rest of us?

Well it turns out that miniaturizing big data is hard. So although companies are keen to be data-driven, the so-called ITOA (operations analytics) tools to achieve this haven’t existed. As well as that, there are a lack of skills in the market who can translate data into business intelligence, or even simple abstraction for IT Managers. So although it is often assumed that rational and analytical data are primary drivers of business decision making, the more complex the decisions the more that managers tend to look at emotional factors as their key catalysts.

This particular assumption was underpinned in a 2016 report titled, “Only Human: The Emotional Logic of Business Decisions”. This was a collaboration with The Fortune Knowledge Group to survey over 720 business leaders discovered that subjective factors such as company culture, values and reputation were at the forefront of decision-making. On the topic of ‘data-driven’, 62% admitted to data blindness, and there is a question mark over how honest the other 38% were to themselves…

Based on the current landscape, if you just want to take a practical approach, and not boil the ocean with some eye wateringly expensive vanilla platform which is as hungry as a blue whale, the recommended approach is to start small and focus on quality of information, not quantity – and keep it regular.

Back in the day when Sonar was being conceptualized, far before the term big data was commonly known about, we were providing complex consulting and transformation services. We could design an amazing bleeding edge technology solution for a customer and make their infrastructure agile and dynamic, but it was the common ongoing questions which gave the customer the most headaches – like ‘what do I have today’, ‘how is it doing’, ‘where could I improve’. If I had £1 for every time I heard – “Well I think it’s like this”…

As a testament to the mindset change of deploying more and more on-premise services, businesses are now consuming SaaS at the fastest rate ever to alleviate datacenter risk and sprawl. With that outlook, Sonar uses the cloud to offload the processing, and enable simple information generation and flow to the organization without adding to the overhead. In this way the big data problem is both reduced in the eye of the customer, but also commoditizes it in a way that hasn’t been addressed previously. You’ll no doubt see the analytics-as-a-service market expand on that premise, and also by the way forecast to grow from USD $4.76b in 2016 to USD $23.49b by 2021*.

Sonar runs true to the theory – start with the basics and do them well; put some basic rules in place, then automate the heck out of it!

*Source : http://www.marketsandmarkets.com/PressReleases/analytics-as-a-service.asp

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