Data helps analyse, understand and improve businesses. You can visualise relationships, find solutions to problems, adopt a strategic approach to problem solving, and make informed choices. It is a field of Big Data that has revolutionised the way we perceive data. Corporate behemoths like Facebook, Google and Amazon use data science technologies for drawing insights into their business and making decisions accordingly. Data science is likely to dominate all industries since every sector of the corporate and governance world can benefit from it. This is because it is a great mix of different aspects of computation and statistics to transform data into actionable information. No wonder then that it is known as the Future of Artificial Intelligence.
It is a good idea to consider GeekLurn’s Data Science Architect Program to understand how the field works. The program offers a 100% placement guarantee and you can start paying the EMI after getting a job. Candidates are given exposure to key concepts and tools, which makes sure they are well-equipped with knowledge of Testing, Hadoop Development, Analysis Modules and Real Analytics. IT and computer science graduates as well as students from a non-IT background can easily build their careers and use data science in the real world.
Here’s a look at a few exciting applications to know why data science is important:
Genetics and genomics research, image analysis in medicine, diagnosis and drug discovery and development can be done with computing technologies. Data science in the medical field is used for predictive modeling for diagnosis as well. Virtual assistance and health bots also use data to provide basic healthcare help in AI-powered smartphone apps. For instance, apps can remind you to take your medicines or sleep on time.
Data science applications in real life include integrating Internet of Things (IoT) to predict potential issues. This in turn makes it easy to monitor problems and analyse the data stream. Data analysis can also be used for reducing costs, boosting profits and optimising production in organisations. The manufacturing line can be enhanced with an autonomous system.
- Risk and Fraud Detection
Banks and financial institutions can leverage data to avoid bad debts and losses. It can be used to analyse past data on expenditure, customer profiling and similar variables to analyse risk probabilities. Management of user data, real-time predictive analysis and customer segmentation are other applications of data science in banking.
- Website Recommendations
One of the most important data science applications is using it to figure out user intent and how relevant information is. It is mainly based on prior search results. This is helpful for internet companies like Twitter, IMDB, Netflix, Amazon and Google Play. Ecommerce platforms can also study customer feedback and buying behaviour to get powerful business insights.
Data science is blended with machine learning to create games that upgrade to new levels as the game progresses. For instance, in motion gaming, your opponent can study your past actions carefully and tweak strategies accordingly. Games like Chess, EA Sports, Sony and Nintendo have improved to new experiences with data science algorithms.
- Image Recognition
Data science and AI can read an image uploaded by the user. It can then extract valuable information from it. The simplest example is when you post a picture with your friend and Facebook suggests whom to tag in it. You may also upload a photo on Myntra and similar products are displayed by reading the image. MRIs and X-rays are also types of data science use cases for image recognition.
- Airline Route Planning
Air-fuel costs have skyrocketed, and airlines are striving to lower their expenses. This is done by operating the profits and maintaining occupancy ratios. Anticipating flight delays, route and layover planning, driving customer loyalty programs and developing marketing tactics are also possible. Companies like Alaska Airlines and Southwest Airlines are already deploying data science in their flight processing.
- Delivery Logistics
Better and more economical logistical roadmaps can be created which is one of the top data science applications in real life. DHL and FedEx find their shipment route, the best transport mode to reach the location and the most ideal time for delivery with predictive tools. Data science can also reduce freight cost, perform price matching, and optimise delivery paths to a great extent, with minimal errors.
Data science can be used to detect frauds and illegal activities in the chunks of data being generated. It helps businesses, government organisations and non-profit entities to protect themselves from monetary losses as well as loss of intellectual property. Data science can also be used to store confidential information with high degrees of accuracy.
An extremely helpful data science application is in the education sector, which helps teachers to modify their teaching style. Problems and potential solutions, identifying student needs, measuring instructor performance and improving the overall curriculum are key roles of data science. You may also learn coding and computer skills, pattern finding and visualisation.
The Bottom Line:
With such increased application across different domains, the future of data science is bright. Businesses can expect highly intelligent decision-making processes. Consider polishing your existing skills or learning data science for a successful career.