How Do Machine Learning and Analytics Compare In Business?

Which Type of Artificial Intelligence Is Right For You?

Machine learning and predictive analytics are both forms of AI, but can offer different benefits for your organisation.

Artificial intelligence could add as much as £630 billion to the UK economy by 2035, as estimated by the Department for Business, Energy and Industrial Strategy. AI is associated with great technological feats of the future, having inspired Hollywood movies and the development of self-driving cars. Unfortunately, 37% of top executives readily admit that they don’t quite understand how AI works, according to HBR. There are hundreds of subsets of artificial intelligence, but two of the key types include machine learning and predictive analytics. This guide breaks down how each could be beneficial for your business.

Understanding Machine Learning

Machine learning is perhaps the most popular or well-known type of AI. The technology uses current data sets to develop models or algorithms. The more you use your machine learning software, the smarter and more effective it will become. Machine learning is available for businesses in either supervised or unsupervised forms. Supervised machine learning requires a little more input from your team members – you’ll need to supply parameters, the desired output and labels for it to function properly. If you have never implemented machine learning before, this is a great option as you’ll retain a lot of control over the software to ensure that it doesn’t make any mistakes.

With unsupervised machine learning, the opposite is true. You simply set the software running and leave it to do its job. Your data will be analysed, from which additional datasets will be created. If you don’t have a large volume of data to leverage, then unsupervised machine learning is really useful.

Cybersecurity relies heavily on machine learning to predict any unusual hacking activity. Your online systems will be continuously scanned to detect the existence and location of any security threats. These can then be dealt with before a security breach occurs.

However, machine learning is also brilliant at analysing marketing performance so that you know which of your channels are most effective. This is a shared benefit with predictive analytics.

Understanding Predictive Analytics

Predictive analytics implemented by a professional data analytics company would certainly include various overlaps with the performance and benefits of machine learning. The main goal of predictive analytics is to provide meaningful forecasts for your data, which might be predicting customer behaviour or sales figures. Therefore, this relies strongly on the need to have plenty of current and historical data available for thorough analysis. When forecasting is automated, this frees up time and effort spent trying to create manual predictions. Instead, you can set your analytics software to spot patterns and trends that could prove useful for your business operations.

Predictive analytics thrives in areas of finance. If you need to give your KPIs some extra attention, perhaps focusing in on the ROI or performance of certain strands of your business, then this type of forecasting is an essential tool.

So, which type of AI is right for your business? This is the question that many executives are struggling with throughout 2020. The best answer is to evaluate what you would like artificial intelligence to do for you, how much data you already have for it to work with, and how much time you have to assess the progress of your AI once it’s in place. If you’re ready to take your business to the next level, then check out what AI can do for you in 2020.

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