In the tech domain, there’s a huge amount of buzz going around big data. Almost every business and company is trying hard to employ data science to rise above the competition.
If you’re planning to become a data science professional, you should know about the industries that will provide you with the biggest opportunity to develop a successful career and to understand what types of job roles will be ideal for you.
Here’re ten industries/applications that implement data science to transform their operations.
In today’s competitive business landscape, if retailers fail to anticipate what consumers want and then provide them with the things, it’s hard for them to succeed. Implementation of data science empowers retailers with actionable insights they need to keep customers happy and returning to them.
Retailers perform a lot of activities by employing data science — from identifying business needs to implementing different technologies to cater to those needs.
For instance, a retail business owner may want to keep customers for longer periods of time in its stores. It can employ data science to develop highly relevant, personalized offers that engage and excite the customers. Every step of a consumer’s journey can be tracked by employing analytics software. The derived insights can guide retailers on how to entice the most high-value customers.
It can also help them predict increased needs for seasonal items so that they can maintain stock of those items before the pick seasons. As a whole, in this industry, consumer data is being leveraged like never before, and offerings and products are hurled on them from every direction possible — all with the help of data science.
The internet industry is perhaps the most notable industry that takes advantages of data science.
Every search engine, including Google, takes help of data science algorithms to provide the users with best results for their searched query within just a fraction of seconds. Apart from search, the entire digital marketing landscape makes use of data science. Starting from digital billboards to the display banners on websites — data science algorithms are used almost everywhere.
In addition, if you’ve ever used price comparison websites, you should have an idea of the convenience of being able to compare the price of an item from different vendors at one place. These websites, powered by data science, can be found in almost every industry like technology, automobiles, hospitality, durables, among others.
In general, people don’t consider the banking industry as an exceptionally high-tech, but with the help of data science, the scenario has transformed entirely. They employ natural language processing and predictive analytics to help customers view information about upcoming bills or banking transaction histories.
Fraud and risk detection is another important application of data science in this industry.
Banking institutions were fed of losses and bad debts every year. However, they collect lots of data during the initial paperwork of their customers. With the help of data science practices, they’re now able to perform tasks like past expenditures, customer profiling, and other crucial variables to analyze the probabilities of default and risk. It also helps them to offer their financial products based on clients’ purchasing power.
Another major implementation of data science can be found in the healthcare industry. Making crucial decisions and drawing conclusions based on data and implementing the medical knowledge in the best effective way possible to improve quality and safety has made possible with a robust data science strategy.
With the help of data science, crucial parameters like brain activity, stress levels, sleep pattern, blood glucose levels etc can be monitored to avert various health problems.
Healthcare service providers also use data science to improve diagnostic efficiency and accuracy. Deep learning techniques are being implemented to read imaging data and to reduce diagnostic failure rates. Another prominent use of data science in this field can found wearable trackers that transmit critical information to doctors about their patients. Compiled data captured over time helps doctors to get a comprehensive view of the wellbeing of their patients. Public health departments also implement data science to prioritize food safety inspections of their facilities.
The energy industry has to maintain a fine balance of providing the right amount of energy at the right time. Too little supply and the customers are likely to find another provider, too much supply and you lose profit. However, with the help of data science, service providers are getting insights about the demands and planning ways of cost reductions in down markets.
By studying historical demand, they can predict accurate energy demands based on anything from the time of day to the seasons and provide the right quantity of energy required. Data analysis also helps them discover new energy sources, avoid power outages, cut costs on drilling and exploration, among others.
Data science, artificial intelligence, and machine learning are the key technologies that help to process products in this industry. Combined use of these technologies help automotive manufacturers attain a lot of things — from improving quality of production to maintaining operations like procurement, distribution to getting valuable insights about purchase prices, delivery reliability, discounts, raw material specifications, hourly rates, among others.
Unquestionably, telecom companies are in a position to capture huge amounts of customer data and by using data science, they provide more personalized services that customers actually want. With the emergence of more devices and advanced technologies for communicating, there’s a need for telecom providers to offer more diversity in their services.
With the help of data science, they’re now able to segment the market more accurately and provide exact deals according to their customers’ needs. They’re now getting insights about almost everything — from data usage patterns, customer care history, video choices and social media activity to website visits, past purchase patterns, search patterns, and more by implementing data science.
Data science is being used by public transportation providers to increase the number of successful journeys.
They use statistics to map user journeys in order to manage unexpected circumstances and provide people with personalized details. Authorities can minimize the distance travelers need to walk to board buses or how many travelers are on a given bus.
In the rail industry, onboard sensors provide details about braking mechanisms, mileage etc of trains. Here, data science professionals attempt to find useful patterns that help them in improving operations. Sometimes they may even discover chains of events which lead to equipment failure, for example.
Across the world, the airline industry is known to face heavy losses. Most of the airline service providers are struggling to maintain their operating profits and occupancy ratio. With the need to offer attractive discounts to customers and increasing rise in air-fuel prices, the situation has become even worse.
However, with the help of data science, airline companies are now able to identify strategic areas of improvements such as predicting flight delay, driving customer loyalty programs effectively, deciding on the class of airplanes to purchase, deciding on whether to land at the destination directly or take halts, among others.
It’s another prominent industry where data science technologies are being used heavily — from tracking average time to accomplish tasks to monitoring material-based expenses.
With the help of data science, construction companies are now able to monitor field service metrics like referral rates and revenue, the lifetime values of customers etc, and identify the parts of business requiring improvement.
In addition, they use data science techniques to identify the best place for projects based on anticipated trends and uses. In some instances, construction material suppliers use geographic data and analytics to offer price transparencies. They use insights derived by the analytics tools to offer lower rates to the customers while reducing inconsistencies in their pricing processes.
The above list is obviously expandable as there’re many other industries and fields where data science is being used prominently. For example, it’s being used in human resources, gaming, marketing, different government sectors, and almost every sector where data gets generated. In the marketing domain, data science techniques are used to decide which items are best for cross-selling and up-selling based on the customers’ behavioral data. In human resources, it’s used to measure employee performance, identify which employees are likely to leave, decide employee bonus, among others.
Another common yet exciting use of data science technologies can be found in image recognition and speech recognition. Today speech recognition products like Cortana, Google Voice etc are getting more and more popularity.
In earlier times, when data science wasn’t in use like it’s today, professionals relied on guesswork heavily when making crucial business decisions. However, with the help of data science techniques and tools, they’re now able to look through massive amounts of data and feel confident and accurate when figuring out innovative ways to deal with crucial things that can help decision makers to take the right decisions in order to increase profitability.