"It's Moore's law on steroids" - Fast data meets Big Data and a whole new technological generation is born

Five years ago in the ever so tech primitive 2012, you either managed Big Data or Fast Data. There was a compromise and trade-off between the two, it was simply impossible to compute vast amounts of data in a reasonably responsive way and a real headache for data solution providers. The subsequent half decade has …

by | October 20, 2017 | bobsguide

Five years ago in the ever so tech primitive 2012, you either managed Big Data or Fast Data. There was a compromise and trade-off between the two, it was simply impossible to compute vast amounts of data in a reasonably responsive way and a real headache for data solution providers.

The subsequent half decade has sought to reconcile that trade-off, to varying degrees of success, and has given rise to the actual applicability of the buzzword, Internet of Things (IoT). Indeed, IoT was a hastily coined term and is irritating to define; after all, any definition that falls back on the word ‘things’ is inclined to be difficult. And despite Google Trends reliably informing that IoT has seen a healthy rise from pre-2012 anonymity to now, it is no new concept.

The first attempt to connect an everyday device to the internet was in the 1990s by Simon Hackett and John Romkey. They successfully operated a Sunbeam Deluxe Automatic Radiant Control toaster via the internet; that certainly made them the toast of the town.

Since then a whole host of devices have joined a network that experts expect to rise to 25 billion devices by 2020. There was an early range of WiFi enabled digital cameras and printers, that morphed to a more sophisticated generation of Smart televisions, washing machines and fridges. It gave rise to a mystified consumer belief that one could talk to their oven as easily as posting to Facebook. There is an element of truth in that belief, though the mechanics are far more subtle even if they retain a relatively simple premise; IoT devices send and receive data which is computed by central systems and used accordingly. The 90’s internet toaster could only receive data, in this case, one command – on. It could not, for instance, monitor and relay the corruption rates of the heating elements back to Sunbeam’s computers and prompt a fresh order of the metal elements from the company’s warehouse.

In theory, the Internet of Things will evolve into the Internet of Everything, as every device conceivable will be adapted to receive and send usable data by a host of data enterprises looking to provide a sophisticated ease of use for the consumer as well as collecting behaviour insights to pedal to businesses. This is all very well and good, but where does this free-fall into connectivity leave the financial services?

The demanding digital space for retail banking

The advanced capabilities to store, collect and compute the vast amounts of data as dictated by a functionable Internet of Things, has largely informed the wider demand of the Right-Now economy. As CEO of DataStax, Billy Bosworth, puts it “customers want their stuff to be relevant to them personally and always available. Instantly responsive, and accessible from multiple places”. This has manifested itself in many guises and is a major contributor to the decline of branch banks. Indeed, this “Right-Now” philosophy, has bred a degree of impatience and frustration among its most avid supporters, namely millennials; in fact, this author refrains from inserting his own recent and deeply inefficient banking experiences.

Do we decry them for that attitude, quoting that patience is a virtue? A virtue it may be, but it is often an inconvenience and, to quote another saying, inconvenience breeds innovation. It’s a burgeoning space that has proven to be deeply profitable and vendors selling data solutions have multiplied.

The present of the Right-Now economy

Another buzzword quite distinct from it’s predecessor multi-channel, omnichannel banking can be added to the multi-faceted Right-Now economy. This banking typifies the ever demanding consumer who has come to expect that they can do all banking functions via any channel. This requires that the bank is able to process the customer’s data and translate it across branch, mobile and desktop. The reality is that the consumer market is driving banks for a greater personalised banking experience which is thoroughly convenient. Indeed, data firms like DataStax, are the unsung heroes of the data revolution. They build architecture that not only houses and distributes data across the globe, but also ensures it is flexible enough to adapt to future trends and regulations. It’s very much a case of ensuring the horse goes in front of the cart rather than banks racing into the future of banking.

But do the data right, and you deservedly trail blaze. Firms like DataStax are the reason that Feedzai can develop the AI to track the spending of individual customers and accessing it in milliseconds for their clients. Their machine learning algorithms are then better able to accurately analyse each transaction and screen them for fraud. The demand for real-time distribution of Big Data, as well as the fast response time required, is a massive data challenge that, as Feedzai succinctly put it, “It’s Moore’s law on steroids – you have to improve just to stand still, to really improve you need to innovate”.

And beyond…

What does the future hold for data? Will 2018 and beyond simply have bigger, faster data capabilities? The answer is quite simply yes. Advances in data technology have made the process cheaper and quicker software. With sound data architecture underneath which is able to accommodate the bigger, faster data functions, it allows a solid platform to build new ‘active’ technologies. This is where innovation will happen. PSD2, will allow a melting pot for accelerated innovation as data holders relinquish data upon request to third parties. They in turn, will test, drive and improve the technology limiting our data processing and completely reinvent the user experience.

Interestingly, where algorithmic machine learning has dominated the fintech landscape for some years, it is perhaps better to begin thinking of machine teaching. “We need to evolve the machines to teach us… to demystify the machine logic so that machines can explain actions and decisions to us in clear, human-understandable text and language”, as the Feedzai spokesperson explained. It is a future trend that will open up all sorts of possibilities, least of all reducing fraud, but changing the way we bank and transact.

Billy Bosworth, CEO of DataStax, points to the market value of harnessing a robust and future-proof data platform, and keeping the “data oligarchy” from total data monopoly. It leaves the future of fintech underpinned by good data architecture, smaller, more personal financial services can offer a bespoke banking experience to reconcile the problem of big data and fast data and lead to a healthy, competitive and forward thinking generation of banking opportunity.


bobsguide was present at the DataStax event on the Right-Now economy and data challenges for the future. 



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