What is data and why is it useful?
15 January 2013
This is the second in a series of blogs that provide an introduction to data, and consider its uses and its impact on the economy. Today’s piece looks at what data is, and how it can be used by businesses. Read the first piece here.
What is data?
Data can be a number, a word, or any kind of symbol which may or may not represent something. In its own right, it is often meaningless – you normally need to know what a given piece of data represents to make any sense of it. But, when used by informed people or computers, it can be used to derive a huge range of information and insight.
Data can come in many different forms, and the context which it sits in matters. Data scientists often draw a distinction between “structured” and “unstructured” datasets, for instance. Unstructured data – such as a stream of words on a website – is often hard to interpret and use. Structured data – which is typically sorted, linked to various key variables, and can be extensively analysed by software packages – is generally more useful, but often requires a lot of effort to capture and create. The form data comes in, and the way it connects with other data, has a large bearing on how useful it is.
Data can come from many different sources, including:
- Data about people – indicated by spending decisions, things they post on the internet, or just their movements;
- Data about machines and objects – many physical objects contain sensors which provide a range of information about them, from their movements to their temperature;
- Data from computers – computers themselves can generate a huge amount of data, from processes and algorithms they run;
- Data from experiments and trials – many experiments, such as clinical trials, generate data of many different types.
This data can be captured in a range of ways, from traditional to high-tech, including:
- Data logging by people;
- Data captured from computers and the internet, from things people write, online transactions and use of websites;
- Data captured through surveys, whether online or offline;
- Real time data captured by sensors and smartphones.
These differences between types of data matter, because they have a large bearing on what can and cannot be done with the data. Data about people, for instance, is far more likely to be private and sensitive than data about machines, and that places constraints on how it can be used.
Why is data useful?
Data is useful for many reasons and in many ways. It can help people (whether consumers or CEOs) to take more informed decisions, it can help companies access vital information on their stock and their customers, and it can help governments engage with their citizens. With developments in various smart technologies, it lets computers manage many things themselves, whether it is an online auction or the temperature of your living room.
Data is useful because it is one of the key building blocks of information and knowledge, which are increasingly valued in today’s world. Many companies – the likes of Google and IBM – exist almost solely to provide information or knowledge to other people, and economic growth is increasingly driven by knowledge, rather than by physical things . The development of digital techniques and technologies, as well as the ever-wider diffusion of digital networks, has made it possible to find more information, more quickly, and to make it more useful, by using data in new ways. In the past, the only way for a local authority to identify houses at risk of fire would be to send round an inspector with a clipboard; now, it may be possible to spot these risks just be looking at patterns in other data . Likewise, customer feedback surveys used to be the only way for firms to find out about their customers behaviour; now, companies can access much more information about many more of their customers just by analysing data from transactions and other interactions. A list of similar examples could go on at length.
Ultimately, though, the value of data depends on how it is used, by individual data analysts, by corporations, by consumers, by governments and so on. Even the most cleverly analysed and visualised data has little value in itself – it must be interpreted correctly by the right people, and used to do something useful, whether it is saving a company money or creating something a customer values. To do this, many businesses and governments may have to change the way they operate, in terms of the way they take decisions, the way they set up their internal operations, the way they engage with clients and so on. Finding new applications for data, making the organisational changes needed to implement them, and finding data-literate people capable of doing so are major challenges for the organisations of today.
How will different industries use data?
The various uses of data apply to almost every part of the economy – hence our description of it as a new general purpose technology. Just as the ICT revolution has changed businesses of all kinds, regardless of what they sell, so data could change every sector of the economy. As examples, consider how data will affect businesses in the following parts of the economy:
The next blog will focus in more detail on how data drives innovation and economic growth.
- Banking – digital networks are likely to transform banking, placing a greater emphasis on mobile banking and most likely reducing the role of branches. Among the disruption this causes, a key challenge for banks will be to build effective relationships with customers without relying on face-to-face contact;
- Healthcare – data techniques have the power to transform healthcare, making it more personalised, more targeted and more productive. By using data to monitor patients either in care or at home with long-term conditions, healthcare providers should be able to ensure skilled staff are deployed where needed, problems are detected more quickly, and patient quality of life is improved;
- Consumer goods – for companies that provide goods to consumers, big data offers an opportunity to personalise their offers around customers. By giving customers access to information about themselves, they should be able to improve choices and tailor packages to customers more closely;
- Advanced engineering – the advanced manufacturing industry is becoming ever more based on complex systems, and geared towards selling combinations of goods and services. Big data enables these services – whether it’s monitoring jet engines in flight or rapidly upgrading products based on live feedback – to be smarter, more efficient and done more productively;
Public services – big data has the power to transform public services, by enabling government agencies to manage records more effectively, and provide a more personalised service to citizens. From taxes and benefits to policing, data techniques should enable public services to become more efficient and more responsive to personal needs.
- Digital economy – the data revolution is already most advanced in the online economy. It has enabled online firms such as Google and Facebook to emerge and grow, has altered the way that much advertising and retail takes place, and has greatly increased the scope for consumer-producer interaction.