Our recent study on enterprise readiness for AI pointed to much work ahead on the underlying analytics platform that could drive progress. But who are the stakeholders for the analytics platform, and how do they relate to each other? I caught up with Klaus Fabits, Sr Director, Pre-Sales Support, SAS North EMEA to understand his perspective on the subject.
The concept of an analytics platform has been around for a while. What’s different now?
I think there has been a step change in requirements for analytics, and in the complexity of problems and solutions. We now have huge amounts of data, including streaming data, and the volume is growing all the time as more IoT devices come online. At the same time, the time available to clean and analyse the data is shrinking. Answers are often required in real time, especially from streaming data. Platforms need to be able to support analytics in database, in stream and in memory, and the requirements for each are slightly different.
That sounds relatively straightforward.
Yes, but this description is the simplified version! As analytical problems become more complex, we will need to combine more data sources and analytics locations. As a result, analysts are looking more and more to machine learning and artificial intelligence solutions, and that has really changed the analytics platform from a “nice to have” to an essential.
We like to think of data scientists as being at the centre of the analytics universe. What do they need from platforms?
I think we can really define data scientists as practitioners in this context. They are the people responsible for writing code, manipulating data, developing models and finding patterns. They also have to be able to present their answers, often visually. Many data scientists are now crossing over from pure analytics, and are now subject-matter experts in a specific field of business too. They know what they can achieve – or rather, should be able to achieve – with the data, but they may well find themselves hampered by process inefficiencies. Old data or data kept in silos and not shared freely across the organisation, long lead times for data and so on – all these are problems that can be resolved with the right platform.
There is still much debate about the role of a chief digital officer or a chief data officer. Whatever you may call them, how do they exploit analytics platforms?
CDOs, also often called heads of data or analytics, sometimes innovation leads, are often the sponsors of projects requiring analytics. They may come from a data or business background, but increasingly have a good understanding of technology. They are likely to be accountable for the success of analytics projects, and are often budget holders. As the sponsors, they need to be able to look holistically across the project and across analytics requirements. Getting the right data, in the right format, doing the analytical work, and sharing the results with others are closely connected. Getting the right platform makes it much easier to see the big picture.
This of course means the platform needs to fit into the overall enterprise IT systems. What do IT decision makers need?
The IT decision makers are those who provide the software and hardware infrastructure that enables individuals and groups to get things done and deliver for the organisation. They are, if you like, the "enablers" of analytics infrastructure, including platforms. They need good guidance and use cases for the analytics economy, and for new areas like AI, to justify expenditures and to identify how the organisation can get the best value for any investment.
Beyond the AI hype, the question is how data-driven innovation can be brought to life. What steps are needed to move AI out of the lab and into business operations? Join SAS experts at an event near you and be inspired to lead your team in the new age of analytics.
Ultimately, AI will be about business impact. When you meet senior leaders – those from the C-suite – what are they looking for?
The C-suite and influencers focus on the whole enterprise. They want to make sure that innovations work for the organisation and support its future financial growth, and they want a way to connect across the company . They are reliant on directors to drive initiatives and bring forward suitable technology, however. The bottom line is that they want something that will work and deliver business benefits.
It sounds like platforms are maybe the best way to manage the increasing complexity in the analytics world.
They certainly provide one answer to that question. However, I think they are more important than that. Platforms are rapidly becoming essential as the only way to be able to ensure governance of both data and analytics, and coordinate work across the organisation, at whatever level. That is the real reason why I believe that we are seeing change, and that a platform is now becoming an essential.
