The internet started by connecting businesses and making more easy simple processes like communicating – for example, by providing email as an alternative to over ground post. More recently. It connected first people’s homes with fixed broadband connections, and then people themselves, with mobile data networks and increasingly sophisticated smartphones. It was only when all of these components were online and generating huge amounts of information, that both brands and individuals started devising ways of harnessing the intelligence that these ‘terminals’ produced.
Artificial Intelligence (AI) has provided a short cut in the analysis of all this data. However, while AI took the problem of large data management and provided a methodology under which data troves could be analyzed, it brought in yet another issue, unique to it. The challenge businesses have now, is the new requirement to sift through the ‘big data’ they have, and to use it in the disruption of their industries, and to drive internal innovation before they are out competed.
What is Big Data, really?
Big data is a necessarily broad term used to capture the outputs from digital processes and machines. The explosion in the number of computers in the world and the things for which they are used has created two types of data structured and unstructured.
Structured data can usefully be thought of as large table of data, organized neatly and relatively simple to interpret.
Caption: Artificial Intelligence helps automate the process of extracting the insights which drive business innovation, from Big Data.
Alt text: AI is an increasingly common component of the ways companies extract value from structured and unstructured data generated by digital processes.
You may have experience with unstructured data in your life, when you open a file attachment as a .txt file, instead of as a Word document, and you see a long list of weird characters laid out in a single block of text. You know that your document is in there somewhere, but it can be hard to find the content because of the way the data is laid down.
Big data tends to refer to quantities of information that are too large and unwieldy to be inserted in to a traditional database. That’s what presents the challenge. The key to improved efficiency and a better understanding of customer desires are in the data. The problem is finding the trends which can unlock those things in information troves that are too enormous to manipulate using traditional techniques.
The place of AI in big data
In 2017, it was estimated that internet users around the world generated no less than 2.5 quintillion bytes of data every day. That is a massive amount of data for any human to sift through, even with the support of advanced computing technologies.
Artificial Intelligence (AI) automates a large part of the solution to the problem. The concept of AI involves data scientists, those tasked with the role of examining the data, using sophisticated algorithms (automated systematic processes conducted by computers) called Neural Networks to examine the information they’re looking at and to extract patterns which create value.
The best analogies can be found in real life. The way a child learns language, for example, is similar to the way AI would analyze a large, unstructured data set. Kids aren’t put in to a classroom for a structured learning process to support them acquiring speech. They observe all the data provided to them, through their eyes and ears, over the course of several years (that’s unstructured data right there!) and use it to form the basis of their own communication.
Over time, they spot trends in the data they receive. ‘Mum’, usually the first word spoken, appears to become appropriate when a familiar woman is close by. ‘Dad’ is said a lot when the loud individual arrives in the late afternoon. Later, more sophisticated associations are established. For example, when people raise the tone of their voices towards the end of a sentence, they are asking a question.
The child collates these associations with verbal responses which appear to replicate the noises made for them. They form a beach head around the words ‘mum’ and ‘dad’ and develop from there, through a process of experimentation.
Neural networks do much the same thing. Imaging providing an AI algorithm data associated with vehicle performance for a fleet of Ford cars in the last 10 years. One reasonable problem to pose might be ‘What was the most common fault to occur in those vehicles’ engines and ‘what data preceded the engine failure?’
In this circumstance, an AI algorithm might identify a that the most common problem was a fuel injectos clogging, and that, in most cases, in the weeks preceding such a blockage, the acceleration capability of the vehicle tended to slow down.
From then on, in circumstances that any Ford car was found to be experiencing a reduction in its acceleration facility, the car could advise its owner to take the car in for some maintenance and suggest to the mechanic that he or she checked the fuel injector cables.
Importantly, humans only need specify the outputs they want. The AI algorithm does much of the processing, of the sea of data, alone.
How AI and Big Data will Combine To Create Business Innovation
So, we have huge stores of data, both structured and unstructured. The data is available and the analysis tools are in place too, all thanks to AI.
For businesses to use it and to establish value for themselves, they need only state the goal.
To that end, we can summarize the various applications of AI in analyzing big data for innovations as:
- Large-scale data analysis: An AI system can be used to browse tons of data at lightning speed. Think of the endless results which can be generated by a single Google search with a relevant query rather than having to put in hundreds of man hours at a library, instead. AI helps companies find the opportunities in their business processes quickly, and move on to identifying solutions, fast. Google’s search product may well be the most advanced Artificial Intelligence system on the planet at the moment, collating as many data points about you as possible and using them to identify the right content on the internet to satisfy your search intent. Google’s entire business model depends on helping you find information quickly and accurately.
- Improved decision making: One thing every business will agree upon is that good information is timely. Firms lose millions of dollars every just from failing to act on information. More often than not, this stems from the information not being readily available. Now that AI is in the loop, such information will be readily available to executives to make a faster decision. Ideally, decision making is entirely optimized – for example when you shop in Amazon and they suggest that ‘people like you’ bought ‘things like this.’ This sort of recommendation is based on AI analysis of similar shopping behaviors and the things that those people bought. Shoppers are provided a better eCommerce experience, the business sells more product and the whole thing is done automatically, using AI.
- Product Development: Identifying market trends and unstated customer needs, from the digital interaction logs they generate interacting with companies are, perhaps, the most important aspect of big data. Netflix, for example famously tracks the shows it’s users watch, which they watch again and again, how much they are ‘binge watched’ and they use all of that information to determine the next program they are going to make. House of Cards, for example, was developed purely on the analysis of this sort of data log.
Automated decision making, improved customer understanding and faster data analysis are 3 of the most popular implementations of AI technology. But the real truth of the value behind AI is that these concepts and capabilities can be applied in any industry from Aeronautics to Actuarial work.
Business that don’t embrace AI and other new tech will soon be left behind by their competition. PWC, the consultancy company suggest AI will contribute $15.7 Trillion to the global economy Not only is AI and big data driving business innovation, those who fail to explore the opportunities it presents will not stay around to garner the benefits.