Big Data 101: What is big data and how can it help business growth?
Hear the word big data, and you’re likely to think “Big Brother”, or at the very least, “Big Business”. Data mining has received a bad rap in the past, but if you buy into the theory that technology, like money, intrinsically neutral, you’ll understand that it is not the data that poses risks, but rather how people use it.
What is big data?
A formal definition of big data is that it’s a pool of large size data sets that’s used to capture, store, search, share, transfer, analyse and visualise related data.
Simply put, data is information. Big data is enormous volumes of data that is sorted, filtered, analysed and stored for the purpose of connecting people with the information that is most relevant to them. In some instances, this data may serve the target audience, and in others, it may serve the advertiser or disseminator. In an ideal world, it would serve both the target and the source by bringing them together in a mutually beneficial way.
Where does big data come from?
There are three sources of big data.
Social Data, as its name implies, is harvested from all the various social media platforms. Clicks, likes, comments and shares are collated and analysed, primarily in order to predict and persuade behaviour. (But more about that later.)
Machine Data is the kind of information that’s generated from radio frequency identification (RFID tags). This could be location data which can feed information to applications like Waze.
Transactional Data keeps track of purchases you’ve made. This way, you can be presented with additional or alternative options based on your purchasing history.
What are the characteristics of big data?
Volume: this concerns the amount of data that comes from various sources.
Velocity: this relates to the speed at which data is processed and analysed.
Variety: this considers the different types of data (i.e. the source, or the form it appears in.) Data is divided into 3 types. Structured data refers to data that’s available within databases, CSV Files, and XLS. Semi-structured data is accessed via word documents, log files, and Emails. Unstructured data is harvested from image files, video files and audio files.
How do businesses use big data?
Big data is essentially a tool that helps organisations make decisions that – when used right, – are mutually beneficial.
For example, most people have a personal or professional profile – or resume – online. By filtering and analysing the data in these profiles, organisations are able to find the right match when they are looking for suitable employees. LinkedIn is a good example of this.
Another example of big data at work to benefit both consumer and business is in CRM (Customer relationship management.) When customers use a product or service, they provide feedback to the source or provider. This feedback, in turn, allows the business to improve or modify the products or services in alignment with the data that’s supplied by their users/clients. This data is stored in the company database and provides both a history and a trajectory.
What are the dangers of big data?
Big data is synonymous with algorithms which are used to record, analyse and ultimately elicit behaviour from consumers. And while big data that’s used to create algorithms can function as an effective filtering system that sorts the wheat from the chaff, it can pose risks to our privacy.
Echo chambers, bubble filters and feedback loops
Big data, along with algorithms, are used for target advertising. Clicks, likes, comments and shares are the data that powers the algorithmic engine. Whether advertisers are promoting a product, an organisation, or a political idea, big data allows them to present users with “more of the same”. This might be harmless enough if you’re looking for “the most comfortable hiking shoes and see what “other customers also bought”. However, it also means that the algorithm facilitates an echo chamber and the algorithm itself can become a “chicken or the egg” feedback loop. Algorithmic amplification fosters the belief that a viewpoint, product, trend or opinion is more prolific than what it really is. In this way, it presents a distorted view of what constitutes balanced news and opinion. Which leads us to…
Misrepresentation of information
Because algorithms aren’t always discerning, they make use of big data in such a way that it can be used for political manipulation and can cause social harm and unrest. Aided by big data, bots can generate fake news, and clickbait is freely disseminated without verification, giving more authority to websites than what is deserved.
This is perhaps where the biggest concern lies. Data brokers aren’t discerning about who they sell data to, and how the data they provide will be used. They will sell data without concern for privacy or vulnerability. There have been incidences where data brokers have sold information that relate to vulnerable people or contexts, like victims or rape, addresses of domestic violence shelters, data of addicts, or lists of people suffering from various diseases.
Is data mining legal?
How to protect your data
Don’t. Eat. The Cookies.
If you visit a website for the first time, they are legally obliged to ask you whether you accept cookies. This is to protect your privacy. At best, cookies aid functionality as they allow the website to collect useful data that can make your life easier. Like the “Remember Me” box that saves information like your login details. Cookies can also save useful information like your “recently viewed” history, and record what you have in your shopping basket but, they can also be used to manipulate you into buying into ideas and products.
Be a savvy seeker of truth
Whether we like it or not, and no matter how many precautions we take, we will generate personal data that can be used to predict and persuade. It is up to us to become savvy when we are seeking information and disseminating news and views. By being discerning when we click, comment, like or share, we remove the marketing targets on our backs.
So, do you think that big data helps or hinders? Big brother, big business or big pain in the neck? Now, you have enough information to decide.
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