Applications of Big Data

Big data is a collection of huge amounts of unstructured, structured and semi-structured data, and this data has exponential growth over time. Nowadays big data plays a crucial role in various fields, some application of big data are banking, education, health care, transportation, communications, Retail and Wholesale trade, insurance, etc.

Banking and Securities

Financial and banking sectors is an important application of big data. Big data analysis helps in this by analysing customer behaviour based on their shopping trends, investment patterns, different other inputs given by them, etc. Big data is used in the financial sector in various forms such as perfecting trade execution, understanding users, streamlining and analyzing the processing of transactions, distinguishing fraud, etc. Analysis of financial sector data also helps in Risk mitigation, Money laundering, Customer statistics alteration, "Know Your Customer", demand enterprise risk management, detecting credit/debit card misuse, etc.

Communications, Media and Entertainment

Media and entertainment applications such as Spotify, Amazon Prime, Netflix, etc. collect data from the users and analyse that data to get insights into what type of videos, and music users like the most, user spending how much time on the website, etc. for making their effective business strategy. Organizations working in Media and entertainment also analyze customer behavioural data for creating detailed profiles of customers which helps in:

• Create content for various target audiences
• Recommend content based on the user demand
• Measure the performance of the content.

Example: Spotify, an on-demand music service use Hadoop Big Data analytics to collect its huge users' data and analyse those data for recommending music to the users, and Amazon Prime also use big data analysis to provide users with a great experience.

Healthcare Providers

Healthcare Providers is an application of big data as healthcare is a department which is also bound to large amounts of data. Big data helps in healthcare industry in the following ways:

• Treatment cost is reduced by the big data as there are fewer chances of unnecessary diagnoses.
• Epidemic outbreaks can also be easily predicted by big data analysis, and then preventive can be taken to prevent its effects.
• Disease can be detected in the early stage and then disease can be prevented, as early stage detection and treatment prevents getting it worse due to which treatment also becomes easier.

Example: Mayo Clinic is an example of using Big Data in the healthcare and medical industry. This technology helps use big data analytics in identifying the patient's conditions and then helps in improving the life quality of the person. At-risk patients can also be identified by this analytics and then medical treatment can be provided to those patients accordingly.

Education

Education is an application of big data as data collected from various courses, faculties, students and results are very large, and the analysis of that data helps in taking decision to improve the functioning and performance of educational institutes. Big data is also useful in providing efficient learning to students, improving the decision-making process, helping students make the best career goals, improving student results, decreasing university dropouts, etc.

Big data is widely used in the education field as it allows us to measure the effectiveness of teachers which in turn helps in providing pleasant experiences to both teachers and students. Big data analytics is also used at the governmental level in the education sector, as big data analytics is used by the Office of Educational Technology in the U. S. Department of Education to help students by suggesting the correct course. Click patterns of students are also analysed to detect boredom.

Example: University of Florida uses IBM InfoSphere for collecting, loading and transporting data from different resources. IBM SPSS Modeler is used by the organization for the data modelling and predictive analysis and IBM Cognos Analytics is used in the case of analysing, examining and foretelling students performance.

Manufacturing and Natural Resources

Big data plays a crucial role in the natural resources industry as it allows predictive modelling which helps in decision making which in turn helps in integrating and ingesting huge data collected from geospatial data, temporal data, text and graphical data.

Big data analytics have successfully revolutionized manufacturing processes, big data also helps in improving the manufacturing process, ensures accurate quality of products, personalizing product design, etc.

Example: Bolls Royce is an example of how big data is utilized in this industry. Big data analysis is used by this company to improve its product's quality and production, decreasing the development time of the product, making the design process more effective, and also reducing the development costs.

Government

The government collects large amounts of data daily, as different records and data of their citizens, geographical, growth, energy resources, etc. are maintained by them. Then this data is analysed and reviewed to make various decisions on developmental plans and to make decisions for the public interest. In public services, big data plays an extensive role in environmental protection, health-related research, fraud detection, analysis of the financial market, etc.

Example: Some of the examples of utilizing big data in government sector are given below:

• Big data is used in the analysis of the huge amount of data received by the Social Security Administration (SSA) from social disability claims and this is received in unstructured form, and analytics are used to process the medical information efficiently and quickly to take quick decision and to detect fraudulent claims.
• Big Data is also used by The Food and Drug Administration (FDA) for analysing and detecting the patterns of food-related diseases. So that faster decisions can be taken which helps in quick treatment and decreases the death rate.
• Big data is also used by The Department of Homeland Security for various use cases.

Insurance

Insurance is an application of big data as it helps assess risks more accurately during underwriting, detects fraud in claims processing, and enhances customer experiences through personalized offerings based on data analysis, such as telematics for usage-based insurance. Big data enables insurers to make more informed decisions, streamline operations, mitigate risks, and enhance customer satisfaction in the ever-evolving landscape of the insurance industry.

Retail and Wholesale trade

Big data helps in trading by doing predictive analysis of rising trends, improving customer service, decreasing market expenses, targeting relevant customers, etc. In retail and wholesale trading, big data applications contribute to data-driven decision-making for overall business improvement, enhance operational efficiency, detect fraud, refine pricing strategies, streamline supply chains, personalize customer experiences and optimize inventory management.

Transportation

Big data plays a crucial role in transportation and makes it more simpler and efficient. Below are some ways in which big data is contributed in the transportation field:

• Route Planning: Big data analytics is used to understand the user's requirements of various routes and different transportation modes and then route planning is used for reducing the waiting time.
• Traffic control and congestion management: Big data analytics also helps in real-time estimation and analysis of traffic patterns and congestion.
• Reduce Accidents: Real-time analysis of big data helps in predicting the more accident-prone areas which in turn helps in reducing accidents and improving traffic safety level.

Example: Uber is an application which uses big data analytics for transportation purposes. Uber has a large amount of data on the vehicles, drivers, users' trips, etc. All this transportation data is analysed and reviewed to get insights into demand, supply, drivers' location, etc.

Energy and Utilities

Nowadays smart meter readers are collecting data almost every 15 minutes. This data is used to understand the utility's consumption better which in turn helps in efficient and better control of consumption of utilities. Energy and Utilities is an application of big data as it helps in better workforce and asset management, which helps detect errors and correct them before they cause any harm.

Big Data & Auto Driving Car

Nowadays, auto Driving Car is a very emerging technology developed by automobile manufacturers. And major challenge in making auto-driving cars is handling and maintaining huge amounts of data collected by the cameras and sensors of the car. Big data technologies play a crucial role in analysing and managing the data collected by cars in real time and allow cars to make decisions based on the collected data. Big data analysis is very useful in the automatic driving of cars without human interference. In an auto-driving camera, sensors are installed which collect data such as obstacles, distance from obstacles, surrounding car size, etc. Then this collected data is analyzed to make decisions on car speed, when to stop, rotation angle, etc.

Big Data in IoT

The Internet of Things (IoT) is a connection of devices, sensors and other objects which can communicate and collect data. Big data technologies are very useful in the management and analysis of the huge amount of data collected by IOT devices. Big data is useful in IoT in the following ways:

• Analysis of sensor data: A large amount of sensor data is generated by IoT devices and big data technologies are useful in the analysis and processing of that data.
• Predictive maintenance: IoT sensors are installed in the machines for monitoring the equipment and Big data helps in analysing that data and predicts the working life of the machine and when the machine requires maintenance.
• Real-time decision-making: IoT sensors are used for real-time data collection. Big data technologies make this process and data analysis faster and more accurate.

Big Data in Marketing

Traditional marketing techniques involve showing advertisements on TV channels, radio surveys, etc. But at that time companies are very little aware of the impact of their ads on the customer. But nowadays big data is very helpful in understanding customer preferences and behavior. Big data can be useful in marketing in the following ways:

• Customer segmentation: Big data technologies are also used in customer data analysis and then customers can be segmented according to their preferences and behaviour.
• Personalization: Big data technologies also help in customer data analysis and providing personalized offers and recommendations for customers.
• Predictive analytics: Big data technologies also help in the prediction of customer future behaviour and trends. And it can help make better marketing strategies.

Example: Amazon collected all the purchase data of people in the world and then design new advertisements and offers based on the analysis.

Big Data in Business Insights

Big data is also very useful in providing insights into business performance and operations. Following are some points which explain how big data becomes useful in terms of business insights also:

• Performance analytics: Big data helps in the analysis of the data of performance of different business operations.
• Predictive analytics: Future performance and trends can also be predicted by using big data technologies, and business can make their strategies and decisions according to the prediction.
• Risk management: We can also use big data technologies in risk identification and mitigation by which businesses can get a clear view of potential vulnerabilities and threats.

Example: Big Data is used by NetFlix for understanding the behaviour of the users, the most liked content of the user, what suggestions can be shown to the user and in which movies or series the user is interested.