Data & Analytics in 3 easy steps. Part One: What is Data & Analytics?
Data & Analytics is the term used to refer to the growing quantity of information available to businesses, information which was previously unavailable, or only partially complete. As new technologies have emerged, what was historically easy to analyse and cross reference has become an unwieldy and impenetrable maze, which is difficult to analyse using hands-on database management and processing tools.
These technologies have meant that information is easier than ever to acquire, but increasingly difficult to make sense of – with multiple sources, storage options and connections in use. In order to carry out an analysis, information needs to be combined, standardised and referenced.
If you imagine trying to combine your weekly food shopping list, with a live price list from all local supermarkets, with nutritional information from your doctor, local hospital and personal trainer, include personal preferences from your friends and family, and then added in the same information for everyone else in your post code, you’d have a fraction of the complexity of trying to use Data & Analytics.
Chief Information Officers, Marketing Executives and key stakeholders throughout a business are regularly tasked with providing reports based not only on historical information, but with predictive outcomes designed for decision making. The problem is that some information might not be compatible with others, and might not be easy to access, and users might not understand what is available to them.
The most common kind of ‘Data & Analytics’ is information about users. People who interact with a website, or who buy from a shop, then become entries in a database. Even in the days of quill pens and ink, information would have been kept by shopkeepers on what was sold, to whom, and at what price. Fast forward to today, and that information has grown to the time, location, quantity, and combination of goods – and innovative businesses use this information to send out vouchers for items we might be interested in, or send us updates on our favourite products and services in the hope of getting us to buy more.
The second kind of ‘Data & Analytics’ is information about states. If you have a fitness tracker on your phone, it’s recording how many steps you’ve taken, your heart rate and sleep patterns. If you watch the weather forecast, you’re relying on ‘Data & Analytics’ to help inform your weather forecaster about likely weather patterns.
Both of these types of data form the overarching image of ‘Data & Analytics’, but both are used in fundamentally different ways. The really exciting opportunities arise when we look to combine both of these data sets (for example, telling us it’s going to rain near one of our stores so that we can stock more umbrellas).
In our next articles, we’re going to look at some of the challenges associated with capturing and analysing Data & Analytics, and finally what this exciting technology could mean for you and your business!
If you would like to find out more about how Data & Analytics could help you make the most out of your current infrastructure while enabling you to open your digital horizons, do give us a call at +44 (0)203 475 7980 or email us at firstname.lastname@example.org.
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