The amount of data created over the next three years will be more than the data created over the past thirty years. Let that sink in for a moment.
This figure, although it seems extreme, will not be a complete shock. The COVID-19 pandemic has changed our personal and work habits, with the population spending more time online than ever before. In fact, according to Ofcom, UK adults are now spending more than a quarter of their working day online. This is, the highest on record. And, with it, generates unprecedented amounts of data, the doubling of video calls no doubt playing a part in this.
Companies have understood that there is a great opportunity here to better understand their consumers wants and needs by analysing available data. However, by collecting an increasing volume of it, businesses also need to make sure that they are keeping sensitive information safe and secure from hackers.
As millions of people use their personal devices for work, data is being scattered across private and public networks and being processed in a more distributed way, making it harder for companies to locate and protect it.
To thrive in this accelerated, distributed and hyper-connected digital marketplace, companies must realise the value of their data while also keeping it secure in a dynamic, rapidly changing environment.
Only with the assistance of automation and artificial intelligence (AI) will it be possible for organisations to achieve both of these things.
Understanding your data
According to research by PwC, in the US today the number of open roles requiring data science skills far outnumber the availability of qualified candidates. So, even if it was possible for humans to process today’s massive data volumes with the necessary speed and attention to detail, there aren’t enough qualified humans to do the job!
Everyday day, Internet users generate 2.5 quintillion bytes of data. A quintillion is a million raised to the power of five by the way… Simply put - the only way to spot patterns in that kind of volume of data - is with artificial intelligence.
With the right AI, you can capture data as it is generated, accurately use metadata to sort it into useful categories, and then process it all to spot patterns at scale and speed. Once you’ve done this, AI augmented human teams can work to derive meaning from these patterns, enabling you to make better decisions, and take action to seize the emergent opportunities you discover.
This means, that with the right approach to data and AI, the right cloud technology - and the right human skills, modern enterprises can:
•Automate the discovery, categorisation and organisation of data, helping to bring it into the production environment faster, often in real time.
•Use enterprise-wide meta-data management - across technical, business, operational and other functions - to improve data organisation, visibility and availability.
•Accurately forecast customer preferences and market behaviour using predictive analytics to spot trends before they fully develop.
•Free IT staff and data specialists from more mundane and repetitive tasks, so they can concentrate on higher value adding activities.
Leading data specialists are now moving beyond relying solely on machine learning, to incorporate genetics algorithms, designed to evolve over time, and other AI-based models which enable continuous improvement.
As your enterprise evolves, the systems which underpin it can become successively more intelligent and better adapted to the job of adding value to the business.
Don't struggle alone
Navigating the current deficit in specialised workers whilst updating or even adopting new analytic software to stay competitive can be overwhelming. As data production and consumption continues to accelerate, so should your business growth, and oftentimes the most effective way to keep abreast is to work with a partner.
A partner should have the expertise and facilities to aid with end-to-end implementation, including capabilities for data categorisation and governance, as well as training. With the right software, you should be able to democratise the role of the data specialist, with key stakeholders able to access the right information to make important and informed business decisions for long-term growth and sustained agility.