Data is often described today as being the world's most precious asset. The technology has taken the limelight in the recent keynote addresses of industry icons such as Michael Dell and Ginny Rometty who have both put it at the centre of their "digital transformation" vision.
And with IDC predicting worldwide revenues from big data and business analytics to reach $260bn by 2022, it's easy to see why.
The same analyst house predicts the amount of data to increase by ten fold leading up to 2025.
A wealth of transaction records, customer behaviour, sensor readings, machine behaviour, security threats, fraudulent activity and more is waiting to be monetised.
One of the big early investors in data analytics, IBM, recently announced a change in its go-to-market strategy.
IBM has now enabled Watson AI - its flagship data and analytics platform - to be deployed across its competitors' environments, including VMware, AWS, Azure, and Google Cloud Platform.
What does this change signal for the data analytics market as a whole?
In a nutshell, that the technology is now more accessible than ever.
We've spoken to members of the channel community, who told us that the cost of entry to data analytics is drastically lower than ever before. And more organisations, including in the SMB market, can benefit from data analytics solutions as a result.
We also pressed them on what specific changes there are in customer buying habits across the market, and how channel firms can differentiate themselves.
'A maturity phase'
Firstly, why is IBM's flagship data analytics platform no longer exclusive to only IBM Cloud?
"The strategy behind that is to try to bring the artificial intelligence capabilities to where customer's data is," said IBM's chief of European channel operations Diego Segre.
Elaborating on the strategic pivot, he added: "As much as we would love everybody to have their data in the IBM cloud, that is not the reality of the world.
"So by taking Watson APIs and features on-premise and into some of the other leading public cloud providers, we allow customers that have their data in those places to still leverage most of what AI can bring them."
Segre said that IBM's decision is also a reaction to the data analytics market now being in what he calls a "maturity phase".
"When we started with Watson API it was mostly around experimenting AI and starting to understand how far it could take us and customers. Now we are in chapter two, which is scaling and getting into the core business processes of enterprise. This is the point at which the pervasive access to AI matters."
Segre's specific advice on how partners can best monetise the trend is to not restrict yourself to only pure AI.
"Look at the whole environment that you want to provide intelligence to," he said.
"Look at security, look at data availability, data governance, transformation and integration and so on. That is obviously a good source of value for customers and therefore money for the partner. All of that integrating with core legacy systems and hybrid cloud environments requires services."
When asked why data analytics is a growing trend now, in a nutshell, the response across the board was: reduced cost.
"There has been a massive drop in cost in the last five years," said IBM's Segre.
"This is something we think will drive more growth in the market."
"Data analytics has come from enterprise," Nuvias' data analytics specialist Wayne Gratton added.
"The reason is that it used to cost a fortune. It wasn't a question of if it would cost a million, but how many millions?
"Now, there are even tools that are free to get on the first ladder of analytics."
Splunk's EMEA CTO James Hodge agrees that the trend's scope has radically changed.
"I've been in this space my entire career, from data warehousing and BI (business intelligence) - those traditional forms of analytics - and I think what's changing is that people are realising that there is value in this machine data," he said.
"Our largest customer takes in petabytes per day into our platform. That would have been inconceivable just five to 10 years ago. And then to run algorithms on top of it - which is only possible because of the advances in computing power - this has been the real change in the last couple of years.
"It has become much more accessible to get into data analytics."
Don't be a jack of all trades
However, not everyone thinks that each firm diversifying its approach to data analytics is the right strategy.
Utrecht-based Viqtor Davis operates in the Benelux, UK and US and also runs managed services in India and Mexico with a headcount of more than 250.
Formed from the recent merger of five European data analytics players, its CEO, Ivo-Paul Tummers, says customers should be mistrustful of partners that call themselves "data specialists".
"This trend is a very dedicated area," he said.
"The problem is that a lot of companies place the data label in front of their house because it's hot and hip and fashionable, but there are not necessarily many service providers that guide a customer through their data journey."
Tummers' advice is for firms to differentiate themselves and really focus on why the market is turning to data analytics.
"Why do we need this? Because we no longer just collect data; we also need to connect to other organisations. Data should be intuitive on the one hand and on the other hand, very trusted," he said.
"So a new trend we see is that our customers are finally embracing data programmes and breaking that up into different projects. So that's why specialised companies like Viqtor Davis exist nowadays.
"There will still be a need for the big system integrators and the big four, and I highly admire them because they can do everything; your logistics, your cloud infrastructure, etc. But we don't only do those data programmes, we go very deep into them."
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