Big Data Blog

Mining data from the data created on the internet is an ever increasing challenge as we are generating a staggering amount of data, roughly 2.5 Quintilian bytes of data every day. With the massive amounts of data that are generated, there have to be ways to filter and sort this data efficiently. There are several methods being utilised right now, such as association. When you go and buy some washing power on Amazon for example, it would make sense for that person to also want to buy fabric softener. This type of association is very simple but the same principles can be applied to millions of different products, thus making it easier to associate data with a person. Another type of method for mining big data is clustering, clustering is similar to association, in that multiple products, items or even ideas, can be clustered together into one group. This one group can then be labelled as a certain entity, where you will be able to find things that relate to that entity. This would be ve...

There are a lot of valuable uses for big data when it comes to companies making a profit, however big data can also be used to solve real life problems and make the world a better place. For example, back in 2014, the CDC which is the Centers for Disease Control, were able to track vital information such as the health, population and movement information to predict the spread of disease. This was extremely handy for preventing the spread of the virus to further areas and inflicting more pain and distress on the population. There is also work being carried out which will be able to predict floodings which will happen within the next 100 to 500 years. This work has been possible thanks to the information gathered from floods in the last two decades and using artificial intelligence to predict these future floods, preemptively saving the lives of countless people. https://insidebigdata.com/2018/03/21/big-data-revolution-data-can-solve-commercial-public-health-problems/ https://hack...

As well as having a lot of benefits, there are also downsides to big data, limiting the harmful factors of big data is crucial to the future of big data and safety of everyone involved. There are groups responsible for monitoring and improving the safe use of big data and to make sure no ethical dilemmas are overlooked. Such groups as the Council for Big Data, Ethics and Society, this group collaborates with the National Science Foundation to provide critical social and cultural perspectives on big data, they do this through public commentary and events. https://bdes.datasociety.net/ http://theconversation.com/six-ways-and-counting-that-big-data-systems-are-harming-society-88660

Big data can be extremely helpful when used correctly and to its full potential, however with the potential for so much good there is also a lot of potential for misuse. For example some credit card companies, based on where a person lives, will give that person a lower credit card rating. This is completely beyond the control of the person, they are living in an area where some people have a lower repayment history, as such they find that their own credit card rating will be lowered. This isn't a fair method as that person having their credit rating lowered may have an excellent repayment rate and is being adversely affected due to the inaccuracy of the data being collected.  http://theconversation.com/six-ways-and-counting-that-big-data-systems-are-harming-society-88660

It may not seem like it at first glance but big data affects our lives every single day in a number of different ways, these include travel, leisure, social media and shopping. For example when there is a traffic incident or roadworks, your phone / gps device will get this information and provide you with information on a quicker route or inform you that your journey will be delayed. When looking for a new programme to watch on Netflix, you will be given suggestions based on programmes others have watched who have also watched the same programmes as you. When shopping online, anything you may have searched for recently, or in the past will be targeted towards you with advertising because they have the information that you have been searching for it recently. All of these are ways in which an individual will be affected by big data. https://channels.theinnovationenterprise.com/articles/big-data-for-individuals

Predictive analysis can be useful at times, however there can be negative points for it also. A fairly recent example of it would be when during the presidential election, Donald Trump only had a 15 - 30 percent chance of being elected president and look at what happened there. The source that claimed only a 15 - 30 percent chance was from the polls, which is where the problem occurs, this is one of several inaccurate sources of information for such an event. These type of inaccurate information sources are the problem with predictive analytics, another example of inaccurate information which cannot be wholly trusted are surveys. Not everyone will answer a survey truthfully, be it lying or maybe being self conscious, using information from surveys such as this will be taking and using false, or inaccurate data and can do more harm than good in conjunction with big data. These are just a few of the different types of discrepancies you can find when using predictive analytics. https:...