We live in an age where technology advancement and science go hand in hand. With the rapid rise in new-age innovations along with its implementation in various new and old business set-ups and expansions, the biggest challenge every industry is facing is the efficient processing of abundance of data generated around the globe. As per a 2011 McKinsey industry report, the volume of data worldwide is growing at a rate of approximately 50 percent per year or a roughly 40-fold increase since 2011. Here comes the importance of Data Science in the picture.
What is Data Science?
Commonly known by the term “big data”, Data Science is the study of the generalizable extraction of knowledge from data. It assesses the behaviour of data in a controlled, logic-led, responsive environment for deriving automated solutions and prognostic models for a given situation, problem or business objective. From Tinder to Facebook; LinkedIn to various online giants like Amazon and Google, Data science is playing a pivotal role in making the data scientist the new sought-after job in the market.
Using large amounts of data for decision making has become practical now, with industries hiring qualified data scientists to handle a wide range of unprocessed data to come up with modern workable solutions catering to their respective market. Gone are the days when companies used to work on software like Excel only to analyse and store data. Even at that time, only some intelligent ventures worked with SPSS and strata.
We need to understand that there is a lot of data but not in a usable format. A data scientist knows the crafts of obtaining value or meaning from large data chunks available within or outside an establishment. The professional knows the art of rationalizing and modeling massive multi-dimensional data in an easy to act on solutions. To give an effective solution, a data scientist should acquire a set of skills including machine learning, mathematics, artificial intelligence, databases, statistics, and optimization, along with the deep understanding of the range of problem-related to it.
Today’s market is evolving at an incredible pace. Tools like Google Analytics, SAP and advanced programming languages such as R and Python are helping data science in a credible way for figuring out solutions to various problems within or outside an organization by linking alike information for future use.
The great names using Big Data or Data Science:
1. Social Media:
We have some great names like Google, Facebook, and Amazon, using effective data science in their day to day operations. If we go in details; we will find that Google is flourishing on the basics of Data Science. Whatever they accomplish or offer is an outcome of Big Data. From google.com to YouTube endeavour, everything is the perfect definition of Data Science. Facebook is another big name in the line of Data Science. Its facial recognition system and even the fact that a user needs at least10 friends to stay active in this social media platform is a well-studied move with the help of Data scientists. On Facebook, every customer’s preferences are stored as Facebook is linked with all major websites that customers use for e-commerce. This helps generate ads as per individual preferences.
2. Aviation and Healthcare
Data Science has massive approach worldwide including healthcare, aviation, logistics, etc. Big Data enables the machine to ask authentic questions which is definitely the base for building predictive modelling, which is effective to actionable business moves. In the healthcare sector, controlled experiments have yielded positive results as they have helped in identifying the causes of numerous diseases. In aviation, now many airlines can effectively run customer loyalty programmes, predict flight delay, monitor air traffic, and decide which class ticket to buy.
3. Logistic companies:
Logistic companies like FedEx, UPS are using data science to increase their operational efficiency. With the help of data science, these companies can figure out ideal routes of shipping their products, mode of transport, best delivery time and many more. Data Science has improved cost efficiency.
This is an era of Data Science where computers are providing better solutions to the problems and better decision makers than humans. This shift can majorly be seen in the world of data- centric finance, where computers are taking sincere investment decisions in a fraction of a second. Financial decisions have become easier for a company my analysing the data from past years and drawing useful insights from it to better their future practices and products. The same is applied for online advertising where millions of auctions are being conducted every day in seconds.
Now, with the significant rise in the data-driven operations in every sector and organizations in the world, the main test every company is facing right now is to make their staff trained and prepared to adapt to the high-end world of data. This requires a fundamental change in the industry working culture, thinking, and approach to a problem. Proper training is required to bring a shift in employees’ mindset toward data-centric decision making by replacing old techniques and practices.
Data Science is here to stay and it is seen that many industries have already set their course to it. Demand and supply can be an issue but it is seen that companies are finding a feasible solution to it also making Big Data a new hot trend at the moment.