The quantity of data collected every day, every minute and every second is simply astounding. According to this 2019 report, Americans alone consume 4,416,720 GB of data every minute of the day. And this is just one part of the world. Imagine how much data is being generated by 4.39 billion people who are connected to the internet all around the world? It’s beyond imaginable.
But what is unimaginable to us is a virtual goldmine to many especially when they have data scientists who are able to mine the tons of data created by human activity and turn it into business opportunities. While data is often in a raw or unstructured form, data scientists are able to apply tools, technologies and platforms to convert the unstructured data into a structured form that can be used in virtually every industry for gains. So not just is it invaluable in the field of IT; but data science has applications in medicine, communication, retail, transport, government, security and a lot more areas. Data Science will soon become an indispensable part of our lives and in this article we attempt to give you an insight into the industries where it would be used most.
According to Josh Wills, Director of Data Engineering at Slack, “Data Scientist (n.): Person who is better at statistics than any software engineer and better at software engineering than any statistician”.
In other words, Data Science is the science or making data useful with the use of machine learning principles, algorithms, and various tools that are used to identify, represent, and extract data.
Telecom service providers collect data from their users phones. This data is then studied by data scientists to study the behavior of customers This allows telecom providers to give personalized services to each and every customer depending on what they need rather than open the same service to the whole country. The industry being accessed by millions of users around the world is also highly susceptible to fraud and data theft. Data science can help prevent fraud by monitoring data activity.
The demands of consumers are growing; and they're growing in a specific and sophisticated way. Software service providers are using real time data to mirror content usage patterns of customers. With data science being perfected, data scientists use the data generated by consumers and put it to good use. Google for example collects & stores each individual user's search history across a host of its services like Google Search, YouTube, Google AdWords, Gmail etc. Online marketers or advertisers use data about a customer’s search history and display real time ads specific to the individual customer’s preferences. All this is possible through the advances in data science.
A very common example: If I search for ‘ flight from Pune to Delhi’ on Google and then I hop on to some other website, immediately I get an ad from MakeMyTrip saying Pune to Delhi flight starting at ₹1999 only. Or if I search Amazon for a Samsung mobile phone, I immediately get an ad about Samsung phones, on the next page I visit, including the price and other specs. All this is possible only through data analysis.
The entertainment industry has made very good use of data science. Netflix, for example, has been using data from its customers ever since its inception; putting analytical tools to task to generate insights about its customers and their viewing habits. Netflix also uses data science to find faults within its own server systems. Netflix uses Density-Based Spatial Clustering of Applications with Noise (DBSCAN), which is basically a clustering algorithm that uses data over a period of time (or as it's called in the industry time series data) to find out which servers are healthy and which are causing latency in providing content to the customers.
AI is being increasingly used for activities that require imagination and creativity. This includes writing movie scripts and songs. A good example of this is the 2016 movie Sunspring that has been completely scripted by an AI bot.
OpenAI has an open-source AI system called ‘Jukebox’. It creates full songs complete with music lyrics and vocals in any genre that a person likes, and it can emulate singers like Justin Bieber to Elvis and Sinatra. AIWA is a program that is made to compose classical & symphonic music.
Major video and computer gaming companies currently in the market have adopted machine learning models to design new games, which improve and update themselves gradually as each individual player uses the game. For example, PETER games learn from their players and upgrade themselves accordingly, which gives advanced players the thrill they look for while playing games and it also gives a feeling of satisfaction to the not so good players who still want to play a game and feel the rush of victory.
VR gaming setups use ML to analyze the opponent moves while playing against computers to generate strategies to defeat the human player.
Energy is the quintessential resource that mankind is dependent on. Data science has only recently been put to use in the energy sector, but the growth has been exponential. From failure modelling, outage detection and prediction to grid security & theft detection; data science is being used everywhere in the energy sector.
Real time data solutions are being used to analyze and predict when an outage might occur owing to weather conditions or for predicting the effect of an asset that has neared the completion of its life cycle. Electricity is a vulnerable resource. Billions of dollars’ worth of energy is stolen or illegally captured from open electrical lines. To prevent this the companies, turn to advanced metering infrastructure which use data science and big data principles in real-time to monitor suspicious usage of electricity over any particular grid or any particular description line. Companies use data science to improve operational efficiency by real-time monitoring of the data such as activity rate power to prevent outages.
Data science has made huge leaps in the automotive sector especially in the fields of self-driving and energy efficient cars. Tesla is already up and about with this new change in the industry. It has also launched intelligent & interactive assistants for its cars so that a car can learn depending on its owner's uses; how fast to charge or how slow to charge and what speeds & routes should be recommended for the least time taken to get to a destination and also to ensure optimum performance of its battery. It has also launched the autopilot for use on the freeways which uses computer vision and deep learning neural networks on the move to analyze every object within 200 yards and make intelligent split second decisions.
Also, data science can be used in developing a new car model. Companies have access to all the data that the consumers generate and the feedback from consumers regarding a product design, which the company can then put in a machine learning model to generate a design that would be perfect for every customer.
Car manufacturers need to know exactly how many units to produce so that they produce according to demand and not in surplus, that may result in loss of precious resources. To optimize production, companies use machine learning models to generate sales forecasts in real time after analyzing years & years of data. Automotive giants like Mercedes Benz and Audi use AI models to forecast the marketing spend for each of their car models depending upon the demographics of a certain city. Isn’t it amazing!
All the amazing things that are listed above are possible only because of dedicated and intelligent Data Scientists, Machine Learning Engineers, Text Engineers, Data Analysts & many more people, who work with data to solve problems, create innovations and in general help us lead better lives.
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