All Businesses collect, organise, and use data on a day-to-day basis. And over time, the amount of data that businesses work with has grown so exponentially that it’s come to be known, simply and collectively, as big data.

What is Big Data?

Businesses of all sizes collect, organise, manipulate, and store data every single day. And the larger the business, the more data it’s working with. Large multinational Organisations, client and customer data, product data, sales and financial data, and a whole host of other data categories.

The term big data means that the volume of data in question is very large: so large that traditional data-processing software is not powerful enough to meet its demands. As data sets grow larger, the tools used to capture, store, analyse, search, transfer, share, and present data must, of necessity, be powerful enough to deal with the data. These problems that are intrinsic to the use of big data are also in some ways synonymous with big data, too.

Why is Big Data and Data Analytics so Important?

The core element of big data is simply that it helps large businesses and organisations work more efficiently. Big data is important to businesses for a number of reasons.

• Storing digital data is vastly less expensive and more secure than storing the same volume of physical data.
• Increasingly faster analytics algorithms that can handle widely disparate kinds of data from a huge range of sources help businesses analyse information rapidly, and use it to make fast, accurate decisions.
• Businesses thrive by developing products and services that their customers want or need. Big data helps companies more successfully predict what products consumers want, and how much they’re will to pay for them.

Applications: What can Businesses and Organisations do with Big Data?

Software analytics is a huge industry that continues to grow rapidly even now. In 2010, the industry was worth $100 billion and growing at a rate of nearly 10% annually. Big data itself is its own industry, as well as being one that is increasingly integral to many others. Some examples include:

Government

Big data is integral to government and governmental organisations, simply because data itself is integral to government. The adoption of big data practices in governments brings advantage such as improved efficiency, innovation, and productivity, along with reduced administrative costs. In government, one of the biggest flaws of big data is the need for collaborative and cooperative working, an issue that plagues governments worldwide.

Manufacturing

The main benefit of big data in manufacturing is improved supply planning and process management, and improved product quality. Big data provides the necessary infrastructure for implementing new production methods such as predictive manufacturing, an approach which can potentially reduce downtime to near-zero, while improving productivity in a range of other ways.

Healthcare

Big data has the potential revolutionise healthcare. One reason for this that it’s increasingly evident that personal genetics and other individual data is inextricably linked to health. Big data therefore has the potential to help the medical industry deliver highly personalised healthcare that both improves the effectiveness of medical care, and reduces waste.

The Cambridge Analytica Problem: Unethical Data Collection and Manipulation

There is another side—another meaning—to big data, where the important question isn’t necessarily how much data is in play. New questions now under the microscope are: how is that data obtained, and what is being done with it? In the wake of Cambridge Analytica, the way organisations collect and use personal data has come under close scrutiny.

Organisations can collect private data in a number of different ways.

• They can outright ask for it, for instance by offering a small incentive to customers who fill in a survey or provide an email address for a mailing list.
• They can collect emails from contact details in online transactions.
• And there are many more possibilities that are simple, legal, and ethical.

We’ve considered the unethical, the illegal, methods of data collection, such as that which was allegedly employed by the private data analysis company Cambridge Analytica—which is said to have used unethical practices to harvest private information from more than 50 million Facebook profiles, and attempted to use that information to influence political events.

The Nature of the Problem with big data

Practices such as these are possible because of the predictive nature of big data. Namely, when you have huge amounts of data on individuals, aggregated into one database, it becomes possible to predict human behaviour with a startling degree of accuracy.

This is the basis of predictive marketing, which manifests itself online in a variety of ways. For instance, buy a laptop computer online—or look at one in an online store—and you’ll be inundated with related advertising on Facebook and other platforms. This kind of advertising is fairly innocuous, and can even be useful. However, the same technology that powers this advertising can, in conjunction with huge amounts of aggregated personal data, also be used to influence people in ways so subtle as to be completely unnoticeable.

The Good and Bad of Big Data

Big data is enormously powerful, with the potential to change and improve all manner of private and public industries, and governmental organisations. But like many things it’s only as good as those who use it: the Cambridge Analytica saga demonstrates the responsibility the big data industry has, in maintaining fair, ethical, and legal practices.