Extra Credit
BIG DATA
created for MIS 2502
Technology is constantly evolving and advancing, bringing the world online and getting it digitized. Everything you do now is recorded as data, from purchasing products online to listening to music,… Billions of people’s information is stored, forming a massive volume of data. This is when the idea of big data is introduced, as a gigantic collection of data. This collection offers an enormous amount of information, and companies are trying to analyze it to understand its customers to provide the best type of products that fit their needs and yields the most profit. According to IDC, big data and business analytics industry is worth around $130B in 2016, while that number in 2012 was just $3.2B. This shows how fast the industry is moving and how important it is becoming to business. Therefore, it is useful to understand big data and to know how to analyze the information.
By definition, big data is a massive volume of data that includes both structured and unstructured data. There are four attributes of big data that is very important for people to understand it, which are Volume, Velocity, Variety, and Veracity (usually referred to as 4 V’s). Volume stands for the amount of data that is generated, while Velocity is the data generating speed. For Variety, it takes into account types of data, while Veracity is how complicated the data is, in terms of structure. With billions of people online, it is not hard to imagine how colossal the amount, speed, type and complexity of the data is being generated. Therefore, traditional technique to extract information soon becomes outdated as it cannot handle the workload. This paves way to new and groundbreaking analytics methods, namely artificial intelligent and machine learning. With these complicated methods, people try to teach computers to identify what a specific type of data represents by showing image or processing language. Then, computers will run millions of simulations, tweaking all the possible variables until they find a pattern that sheds light on the problem. The better and the more accurate the analysis is, the more profitable it is for the company. As a result, many companies are on a run for getting better artificial intelligence and machine learning by investing billions of dollars in the field.
Business companies are not the only entity that benefits from big data. Users of big data can consist of educators and government. Educators can use the information extracted from big data to identify at-risk students to help them make progress. They can use data to improve the system for evaluation and support of teachers and principals. Government, meanwhile, utilizes this information to improve the infrastructure of the country, ranging from managing utilities, running agencies, solving the problem of traffic congestion to decreasing crime rate.
As a coin has two sides, the more growth big data is assimilating, the more controversy associated with it arises. Currently, there are three main problems with big data, which includes data security, data discrimination, and data privacy. The first one occurs when company doesn’t have good protection to their data store so that hackers can steal information. The second one involves a balance of public and private information of users, which should be determined by users. Not by apps or services providers. Most recently, the infamous incident of Facebook and Cambridge Analytica raised even more alert about data privacy. Cambridge Analytica is a consulting firm that worked on several high profile politics campaign ,including that of President Trump, used the social media company’s platform to harvest the data of 50M users. The last one happens after data is understood, raising the question that will a company, with knowledge of its customers, discriminate them based on certain characteristics.
As an MIS major student in specific and as a tech-interested person living in a technology era, I feel the need to understand big data and how to make use of it. For my future career path, since I really like math and statistics, I would love to work with data and thus, have to constantly update myself with new knowledge about this ever-changing field. Moreover, by having a good understanding of big data, I can protect myself from any problem associated with it, as well as be responsible when using and working with data.