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The phrases ‘machine learning’ and ‘big data’ get thrown around a lot these days, but they are definitely terms worth understanding. Embracing these advances in technology can potentially help you gain or keep a competitive advantage. Read on to learn where they’re going (and maybe pick up a useful tip or two).
By 2020, it is estimated that 1.7MB of data will be created every second, for every person on earth!
From what you’re ordering for dinner, buying for your partner’s birthday, where you’re travelling or secretly googling while in that boring meeting… your data is being captured around the clock. While this might seem intrusive for some, others accept it as they know it means they’ll be targeted with content and advertising that better matches their interests.
While this data is a marketer’s dream, it is also incredibly useful from a broader business perspective. A deeper understanding of your customers and their needs and wants allows you to provide a more tailored service that will hopefully lead to a long and lucrative relationship.
Digitally native businesses have always done this, but traditional businesses are now catching up. They are recognising that with the right platform, they can better serve customers if data is collected and understood correctly. Uber is a great example of a digitally native business that leverages the data that it collects from its users and drivers. Their terms and conditions clearly outline their intention to use your data to improve its service offering. Uber has also looked at incorporating machine learning to further improve service.
Speed, capacity and connectivity are just a few of the benefits of 5G. This will provide even more data for businesses to feed their machine learning, along with the faster transmission of data from the sensors that enable IoT capabilities. Office jobs will also become less repetitive as machine learning picks up the slack.
Currently, supervised machine learning is the norm. This entails algorithms using labelled responses to learn from data, whereas unsupervised learning does the same thing but without the reference point of labelled outcomes. While not yet as accurate as supervised learning, unsupervised learning does have its applications when it comes to discovering a data set for something where your desired outcomes are not already mapped.
Gone are the days of gut feelings and a person’s level of seniority being the deciding factor in decision making (well for most businesses anyway). The capture of real-time data (or close to it) enables competitive advantages, and smart businesses are well aware of this. Data captured from prospective and current customers can tell businesses a lot – what’s trending, what consumer needs currently are (and how they differ from previous periods), what the market’s appetite for your product or service is. This information is being used alongside research from third-party businesses to create robust, meaningful strategies that guide businesses and prepare them for the future.
It seems as though now is the time to be a new generation data scientist. Better UX for machine learning means less technical skills are needed for many data science roles, but people within these areas are more frequently needed to work across silos and be more integrated into their business – this can mean interpersonal skills, high levels of communication and collaboration are now critical for a team’s success.
There is a lot of information about machine learning and big data and our team love to talk about it. If your business requires of a plan for how you can utilise these elements to gain a competitive advantage, we’d love to hear from you.
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