The large volume of data is called big data; it is the term that describes huge amounts of data that is being generated from different sources in a real-time environment. In today’s world, big data has its footprints in almost all the fields of science from biology, astronomy, social sciences, etc.
In biology, large databases record proteins and genomes; in astronomy — petabytes of data from sky surveys are received; in social science — millions of posts and tweets go around the internet. The flood of data can bring out human insight and analysis, which can make sense only with the help of advances in computing. On top of that comes information technology, a field that is committed to computational advancements to improve the quality of life.
Data has always been an important factor for humans to analyse and make decisions. Without data, we cannot have the knowledge, and without knowledge, we cannot analyse or predict future outcomes. The usage of data leads us to the emerging field of computer sciences known as Artificial Intelligence.
Underpinning all this is the explosion of data. Data is growing faster than ever before. By the year 2020, it’s estimated that every human being on the planet will be creating 1.7 megabytes of new information every second! There will be 50 billion smart connected devices in the world, all developed to collect, analyse and share data. This data is vital to Artificial Intelligence. Computer Scientists define AI as a journey, and the journey to AI starts with ‘the basics’ of identifying and understanding the data. Where does it reside? How can we access it? Of course, some data may be ‘difficult’ – it might be unstructured, it may need refinement, and it could be in disparate locations and from different sources. Then that data will be processed through different types of ‘data pre-processing’ stages.
The next step in the journey is identifying and understanding the patterns and trends hidden in the data with smart analytics techniques. Only once these steps of the journey have been completed we can progress to AI and machine learning, to gain further insight into the past and future performance of organisations, and to help solve business problems more efficiently. This is where un-happening happens, and manpower reduces, one well trained model help predict trends for the next 50 or more years. This is how data is driving the future and will be the fuel of the future as quoted by many ML Scientists.
Muhammad Nadeem Jahangir
