Technology has become the underlying necessity in our day-to-day life without us realising. You use it to set your alarms to get up in the morning, to remind you of that doctor’s appointment next Thursday afternoon, to post pictures of your over-priced lunch on Instagram, to communicate with your friends on Facebook, to listen to music at the gym on Spotify and the list continues to grow alongside the rapid advancements. The point I am trying to make is that we have become very dependent on technology. If every piece of equipment with an operating system stopped working tomorrow, life would become very difficult for us but even more so for hospitals and airports.
With that thought in mind, could you go without using your mobile phone for more than a day? How about giving up browsing social media for a week? If you attempt these challenges, you will be met with the realisation that it is a lot harder than it looks. You become aware of how much you need technology. This new series aims to educate and inform students about all aspects of technology, to make them aware of how much we use it daily, how it truly impacts our lives and some of the dangers to look out for. Over the next few weeks we will be discussing important topics relating to all this. If you have any topics you would like us to cover, please feel free to email us at email@example.com.
The first topic we will be discussing is Big Data, and how it is used within our lives without you even realising it.
It is estimated that we spend at least 2-3 hours of our day browsing social media. We are engrossed with the consistent flow of content that is given to us as we scroll on the screen. It is content that we enjoy, and it is content that is suggested for us. But have you ever stopped and wondered how exactly those videos ended up on your recommend? Or how advertisements about your interests or hobbies show up on your timeline? You guessed the answer; it’s all because of Big Data. The definition of Big Data is meant to describe a large volume of data that inundates a business on a day-to-day basis. This information can give businesses an advantage over their competition if used correctly. To explain how this is possible, we must dive deeper and explore the key characteristics of Big Data by using the three V’s:
- Volume – The quantity of generated and stored data. The size of the data determines the value and potential insight and also whether it can actually be considered big data or not. Remember it’s not important about the quantity of information collected; it’s what organizations do with it that matters.
- Variety – The type and nature of the data. The nature of the data must be relevant to the end result; irrelevant data can be eradicated so the focus can be on the information gathering.
- Velocity – The speed at which the data is generated ad processed to meet the demands and challenges that lie in the path of growth and development.
With these three characteristics combined, businesses can have access to a large volume of relevant information in a short period of time. This information can be used to cut cost and time reductions, begin new product development and optimize offerings and help to make smart decisions. It can also help businesses determine their root causes of failures & issues, track trends and patterns that relate to human behaviour and recalculate their entire risk portfolios in minutes. This will give them the benefit over their competition and allow them to excel in their field.
That is how businesses use Big Data, but now let’s discusses how it affects you on a day-to-day basis. We are going to explore two different businesses that are very well known and used by a majority of people. The first business is Facebook.Having 1.86 billion monthly active users, certifies Facebook as being one of the most popular social media companies today, but it makes them a magnet for advertisers. In February 2016, Facebook made a massive change by replacing the standard like button and introducing 6 reactions which allowed users to express how they feel about a post made. Mark Zuckerberg expressed how Facebook needed a more nuanced way for users to interact with posts, as not every post is likeable. But this is not the real reason why he introduced it.
Facebook shows you advertisements based on your reactions to posts. If you react with angry or crying to a few posts then you are less likely to see advertisements, whereas if you react with like or love then you are more likely to see advertisements about products based on your interests. This information was discovered by Big Data. By carrying out different methods of advertising, this information was discovered. Hypothetically, Facebook could put out a basic advertisement to 10,000 active users who have reacted to a post with anger and out of those 10,000 users, 250 users clicked it. They then put out another basic advertisement to the same users but whenever they react to a post with love, 5,650 users clicked it. Comparing both statistics, it is evident that there is a greater chance of users clicking on shown advertisements whenever they are happier.
The next business we will talk about is Spotify. As of September 2016, Spotify had over 40 million paying subscribers. This is just below 50% of overall Spotify users. Introduced in July 2015, Discover Weekly has become one of the most used features on Spotify with each user having a unique playlist updated weekly which recommends artists based around the music they listen to. Big Data is actually the one who is picking out your recommended artists.The information required to piece your playlist consists of how often you listen to artists, the genre those artists belong to and the number of different genres that you listen to. With this data, algorithms are used to pick a playlist based on your listening habits. If you only listen to one artist in one genre, you will get other artists recommended in your genre, whereas if you listen to a number of different artists across different genres then your playlist will become very varied in the music that appears.
Spotify use their subscribers listening patterns to see what the most popular songs are in all regions of the world. There is a feature is called the Top Charts. Using the information about listen patterns, Spotify create playlists targeted at their users. Other media streaming services such as Netflix, does the same by collecting big data from its’ 93 million users. They recommend the top movies based on user’s viewing habits. Whenever you finish a movie, they recommend another based on what other users watched after.
These were common examples of how business that we use everyday use Big Data to help influence our choices without us even realising. What we have learned is that Big Data is here to stay.