Humankind has made very significant advances in science and technology. However, a large number of questions still remain unanswered.
The very last science that has been discovered by humankind is computer science. The world’s first computer science degree program, the Cambridge Diploma in Computer Science, began at the University of Cambridge computer laboratory in 1953. In the eyes of science, the last child, computer science, is changing the world rapidly. Not only this change is not a simple linear change that has a straight relationship with time but also it is an exponential one which means one change leads to thousands of changes. Let me explain with a clear-cut example. At first, computers were not as powerful as they are today, improving their hardware led to a complex calculation in their software and different methods of paging in CPU and memory introduced, which results in operating systems that paves the way for more scientists to conduct their research and tackle the problems along the way.
For the first 20 years of the existence of computer science, there were no advances toward storing data, hence the potential improvement was slower than the era of storing data. By storing data human being has come to realize that cooperating and collaborating with computers would be considerably beneficial regarding time and energy saving, so by getting deeper and using data as a powerful tool the ever-changing environment has become more obvious and even more tangible for elderly people who undergo these changes during their life.
In today’s world, the presence of millions of billions of data generated by people and companies all around the world plays a vital role in human lives. For instance, for buying not relatively important home appliances you have access to a vast variety of websites and applications in a fraction of a second without having to commute to different stores.
Data usage and continuously generating data indicate the importance of data and more importantly data about these data. Consider a textbook example of a Netflix user, a user knows there are a large number of movies available in the database of Netflix and also knows he/she has no time to watch all of them, which contributes to categorizing movies based on his/her favorite genres. Although the user minimizes his/her choices to a unique genre, there are still a large number of movies that are available to choose from. Here the remarkable role of metadata (data about data) emerges. For example, a user can make his/her decision based on the rating of other people who have watched it so far or get a recommendation by Netflix itself based on the users' watch list.
Or maybe even more fateful decisions, such as doctors make for patients. Many countries are struggling with shortages in healthcare staff. Therefore, time management for a heart surgeon is highly valuable; because lots of patients are in the queue to be checked. In this regard consider a patient with hypertension and there are a large number of values need to be checked by the doctor to realize at what time of a day the patient has higher blood pressure. Thanks to the advancements of technological development, data scientists have made it possible by visualizing data, and the doctor can make a more accurate decision in a relatively shorter time just by a simple look at graphs and plots.
Data-driven decision making has been evolved in the past decade. For instance, it could be buying a product from Amazon found on the number of sales or comments of other people who already bought that product or to choose your university hinge on top rank universities provided on the web or making decisions in medical science stand on the at hand data of other patients suffering from the same disease. None of these decisions could have been made easier without using data.
As I mentioned earlier, data is rapidly increasing all over the world, and having data about these tremendous amounts of data is preferable more than ever, which is possible by the presence of data scientists. Moreover, data scientists can predict the future based on the gathered data of the same situation in the past.
I live in Florida and I think it would be interesting to make a typical example regarding this state. During hurricane times people rush at stores such as Walmart to provide food and their necessary products. We all know requests for bottled water would dramatically increase but the main question that remains to be answered is how much it will increase? Data scientists can answer that based on the exact same situation in the past and the data they have to answer such questions.
The New York Times reported that: the experts mined the data and found that the stores would indeed need certain products — and not just the usual flashlights. “We didn’t know in the past that strawberry Pop-Tarts increase in sales, like seven times their normal sales rate, ahead of a hurricane,’ Ms. Dillman said in a recent interview.’ And the pre-hurricane top-selling item was beer.”
In my opinion, people are nothing but the things they are in favor of and the things they hate. Have you ever thought why people are in favor of the products of big tech companies like Apple, Microsoft, Google, Amazon, Facebook, and Netflix? To be honest these companies already know our taste and they constantly try to optimize their algorithms to be more concise. For example, apple improves IOS based on its user experience database, Microsoft shows news base on your location and optimizes its operating system based on available data, google knows the exact home and work location and show you the advertisements that you want to see, Amazon suggestions are based on the products you searched by far or bought so far, Facebook throws data at you based on our Likes and Netflix recommendations are based on your search and watched list.
We all have seen that data have revolutionized our lives, we can come to the conclusion that the future belongs to data and data only. Therefore, picture the future in your mind’s eye and comment your point of view about the not too far future in this post.