In a recent post, I wrote that Big Data and Analytics are at the heart of most of the conversations I currently have with the industry folks I’m connected to – and that’s certainly not changed.
But what I now also sense – backed up by recent research from Forrester – is that there is a distinct new theme emerging: that of the need to integrate data and tools, so that the success of Analytics isn’t reliant on major (and expensive) data migration and infrastructure configuration projects.
This is ultimately about enabling data scientists in a business to spend a lot less time preparing data and more time extracting business value from it – and the upshot is that the Analytics challenge is no longer about the journey to the cloud, but the journey to the clouds.
Here’s what I mean:
Analytics: key but chaotic?
According to the Forrester research, some 45% of respondents say data and analytics will become the most important factor for business competitiveness in the next three years – a definite strategic asset.
So you can almost feel the frustration radiating out of the report when, simultaneously, they complain that they struggle with integration and core data management capabilities, citing a lack of platforms for developing advanced models, and poorly integrated tools.
Essentially, the potential power of Analytics to accelerate insights and support ‘right first time’ decision-making is being hamstrung by these integration issues.
So is there a roadmap for change?
In short, yes – and it involves fixing the two problems that are hampering the evolution of Analytics more than any others: the limited supply of quality data ‘fuel’ (because it relies on selectively centralised sources) and the poor accessibility of tools to build, tune up and fix the Analytics ‘engine’.
Unified, not centralised – the next Analytics chapter
This is achieved by making data and tools available across clouds, unifying access to what is in all of them and producing a complete view of data in every form, across every source. (Remember – clouds, not cloud!)
In tech terms, what this translates to is an open, extensible data and Analytics platform that runs on any private or public cloud and in any on-premise or hybrid environment, and makes the data Analytics-ready wherever that data resides.
Sound like a big ask? It does – but it’s not only already available, it’s also already generating proven business uplift by unlocking and managing data value with far greater trustworthiness and far less effort than was previously possible.
Unified data and tools: where’s the Analytics value?
So what does this unified approach to Analytics data and tools bring to the party that businesses and their data scientists should be especially interested in?
Firstly, as I alluded to earlier, it enables data to be made Analytics-ready without going through a complex, costly and risky data migration process, as the data is usable wherever it already resides.
Secondly, unified access to data means that it’s possible to access greater volumes of data to ‘feed’ inbuilt AI processes, in order to better automate data classification and so enable data scientists to focus on more business-critical tasks.
Thirdly, it makes governance less manual and more effective, by enabling data access to be controlled directly from the data’s source, facilitating more straightforward definition of rules to prevent data misuse (GDPR, anybody?)
And fourthly, its multi-cloud architecture makes it possible to analyse data from public cloud apps that are, potentially, a hugely rich source of untapped insights.
Show me the proof…
Unified, multi-cloud data and tools are a leap forward for Analytics – and they’re already a technical and business success story.
IBM’s Cloud Pak for Data, for example, has been proven to deliver a 77% improvement in both strategic planning and business efficiency – and it’s also been made more accessible to many businesses through Cloud Developer Credits.
Proof, if any were needed, that when clouds work together, they can deliver gold dust, not just a silver lining.