Big Data – Big Opportunity

Author: Nikolina Zeljko | Category: News | Posted: 05.06.2017
Writer: Dario Jurčić, NSoft What is Big Data? Today we often hear this expression, although many will say they are not sure of its meaning. If you google it and try to figure out what Big Data is, maybe you’ll come across some explanations you will not understand. When you try to explain it to the person who has never heard of it, the simplest way is usually the best way. In this case, it’s “three Vs of Big Data”. If you have a problem with any of the “Vs”, you have a Big Data problem: the speed of data processing - Velocity; the amount of data - Volume; and the diversity of data - Variety. Before, the amount and speed of the data were the most problematic. However, by reducing the disks price and increasing the variety of data storage, the problem of a large amount of data is largely solved. By increasing data flow (e.g. 40Gb Ethernet), the problem of data overloading is no longer such a challenge. The biggest challenge for Big Data is the last V - a great variety of data. There are many data sources and the generated data is not the same - some are structured, some are unstructured or partially structured and there are also audio and video files, various logs, etc. Today, simple activities such as reading a book, watching TV or listening to music generate information about our activities. Every form of human communication leaves a digital trace, starting from an e-mail, to conversations over a phone or chat over Facebook. Why do we then say Big Data - big opportunity? One old saying goes: “Knowledge is power.” For example, knowing what your clients like, what are their habits, demographics, forecasting their purchases give you the power of managing your business in a best possible way. Of course, it’s difficult to derive meaning and business value from the large amounts of data coming at a high speed. Here’s the big opportunity for Big Data as well as perhaps the most wanted, best-paid job of our time - data science. Generally, it can be said that data science is extracting knowledge from the data. Data scientists explore complex problems based on knowledge of disciplines such as mathematics, statistics, and computer science. Value is derived using analytical knowledge and tools such as R and SAS, technical knowledge such as coding in Python and SQL. Yet, perhaps the most important thing is what they bring with a non-technical characteristic that distinguishes a good and a bad data scientist - curiosity. According to reports from companies such as Deloitte, world companies will need more than a million data scientists in 2018. Depending on niches, some companies will value data scientists more, some less, but average annual salaries in USA range between 100 000 and 200 000 $. No wonder Forbes named Data Scientist the best career selection in 2016. Still, many will say that everything this hot must cool down. However, keeping in mind all the above - that sources, amount and speed of data are drastically increasing from year to year, that companies are increasingly looking to extract business value from data, it is certain that Data Science is a great career choice that will provide you with money and exercise your intellect. If you are a beginner, I recommend that you visit the DataQuest.io site and take advantage of free introductory lessons, and if you decide that Data Science is the choice for you, the cost of learning is very favourable. If you have the knowledge I mentioned earlier and have not yet decided which way to go, my advice is: Go for it. The only restriction is your curiosity.