After 7.5 million long years of computation the answer is 42. Deep Thought points out that the answer seems meaningless because the beings who instructed it never actually knew what the question was.
And no, there is no such thing yet as a ‘single entity’ that contains all knowledge – that is where big data comes in. So begins an interview with Paul Sonderegger, one of Oracle’s Big Data Scientists which frankly, like big data, is too big to comprehend.
He was in Sydney, Australia to give the opening keynote titled The Rise of Big Data Capital to delegates attending the Big Data & Customer Experience (CX) World Show 2016.
The Bostonite’s premise is that data is now a kind of capital, on par with financial capital even though it cannot yet be shown on a balance sheet. And just like financial capital, having more than your competitors is necessary but not sufficient. Companies have to embrace new tactics like platform competition and network effects to create sustainable competitive advantage as their industries become ever more data-intensive.
And because Sonderegger is such a long surname the rest of the interview is paraphrased!
We generally chat about big data
There is still a mystery about big data – what is it, what does it mean, what can it do and why is it the topic of so many corporate conversations right now. Big Data is not a specific set of data but rather the whole is greater than the sum of the parts. Combine data from disparate sources, see what insights and relationship come out – it is all about capture and use of any data.
Data fulfils all the economic definitions of capital and can be a source of competitive advantage. Data in use creates more capital and sustained competitive advantage.
Data is not yet on the balance sheet as international accounting standards don’t cater for that. But look at any business and regardless, it is valued by a market cap that greatly exceeds its balance sheet value. Call it goodwill but in strong companies its likely to largely comprise data and intellectual property that can be sold.
The world is embracing digitisation of everything – that creates more data assets and the best thing to do with those assets is to produce new goods or services or create a sustainable advantage based on those analytics. We can create unique value – that no one else can offer.
Data comes from activity – it is not naturally occurring. You need to set mechanisms to capture it, not for the sake of it but for the purpose of it.
Data tends to make more data – it breeds as it is fed it into other data and creates new relationships and contexts for analysis - and that’s why the cloud is the best place to store it. That is where another ill-defined terms comes in – the cloud is simply highly scalable, pay as you go storage you can use to create massive data lakes as the precursor to analysis.
Data platforms like Microsoft Azure and Oracle Cloud tend to win because they are focused on data and have the economies of scale. We hope Oracle is seen as one of the preferred development platforms and we have bought it to huge enterprise, governments and now to the smaller end of town because we can deliver from the cloud – on demand and pay as you go. You don’t need to own the asset (hardware, software, maintenance) to get the benefit of it. But you do need to own your data!
Data enables a whole new world
You simply have to dream up new uses for old data. Look at things like usage based insurance – now it can be tailored to you based on big data and your granular usage data.
Look at retail where transactional data, government census data, store layout, weather data and social media can help to make better predictions about the success of a product launch – in considerably less time than in the past. The news here is in recognising the correlations and connections between relevant data – what you in the past may have called gut feel.
The problem is that marketing has been measured on its success – often weeks or months after a campaign. That can be very wasteful. Now you pool your data in a data reservoir, mix in other data and you can come close to real-time predictions enabling you to use that feedback, for example, to modify advertising spend or reach.
What is the secret sauce to big data success?
Data scientists are currently a pre-requisite as they can innately identify how to link disparate data and how to hypothesise to get results. But Oracle’s Public Cloud brings a lot of open tools (like R) down to the smaller organisations that don’t need data scientists – they just need insights from mixing their data with the reservoir.
We run the world’s largest third party reservoir that comes from thousands of sources. Its scope still amazes me.
The secret is that this reservoir when mixed with a company’s internal data produces insights especially for it – not its competitors (hence the reference to capital earlier).
What about privacy?
Data is all about trade-offs. You reveal something about you in order to gain a benefit. Privacy however needs to be the cornerstone of how it is used, stored, combined and sold. You will find that good, proactive data governance, especially in larger enterprises is a major issue that is taken very seriously.
It is tempting as a data scientist to use big data for good like improving the quality of life, or extending it but there are rules on how deep you can delve. We all need to do a lot of hard thinking about data privacy and governance – especially where clouds can traverse so many countries.
The ‘Sheriffs’ of the future will be the Chief Technology officer (CTO) who will ensure risk and compliance issues are observed.
And we need to be better at protecting and redacting personally identifiable information.
The regulatory challenges were significant for both sides as it is not always clear when a company has a monopolistic hold on data or when it is abusing that to hamper competition. It may not be clear, but the fact that it is possible is what is perplexing the regulators.
Where is Australia in the big data race?
Australia is still very much in the toe-dipping mode although there are some standout users. It is about three years (subjectively) behind the US and perhaps two years behind Europe.
Asia is a two-speed user. There are some real entrepreneurial tigers in South Korea, China and Singapore but on the whole it is behind Australia. The focus there is on data as capital to produce competitive advantages.
Where is all this heading?
It is more about asking the right questions a.k.a. 42. It is more about defining what data is needed and creating a discovery environment. The world is becoming ‘datafication’ focused – capturing everything it can from smart homes, devices, IoT, and so much more.
Analysis and data science will be used to help that data interact with each source and it will change everything it touches.
Big data is about the future – it tells us what could be.