Big Data Applications in Everyday Life: 11 Use Cases

Writer : Michael Aurora EG

Big Data Applications, Because of our reliance on mobile devices like smartphones, smart cameras, smart tablets, smart wristwatches, and smart speakers in our daily lives, we've amassed a massive amount of digital data.

Big Data Applications in Everyday Life: 11 Use Cases

However, how is it possible to make sense of such a confusing volume of data? It's here that big data really shines. There have been numerous advancements in big data technologies and tools to assist in overcoming these difficulties, and businesses are now reaping the benefits of these advancements by implementing them to expand their operations.

What is Big Data?

Large amounts of structured and unstructured data that are constantly being generated by a company are what is meant by the term "Big data," which is often used colloquially. The three Vs - volume, velocity, and variety - are the most commonly used to describe it.

As a once-trendy idea, wearable technology has become an essential part of our daily lives. As a result of Big Data, concepts like what consumers want can be measured and inductive reasoning is made easier. Interestingly, this technology is being used in almost every industry to predict how people will live and what they will buy in the future.

Applications of Big Data

We've highlighted 11 industry verticals that are embracing Big Data, as well as examples of how they're using the technology, in this post.

1. In Banking

Big data has improved the efficiency of banks in a variety of industries, whether it's cash collection or financial management. The bank's revenue has increased as a result of the technology's application, and the bank's ultimate insights have become more clear and comprehensible as a result.

Big Data can be used for a variety of purposes, including detecting fraud, streamlining the transaction process, improving customer understanding, enhancing trade execution, and providing a better customer experience.

  • When it comes to Big Data in the financial sector, Western Union is an interesting case in point. The company processes over 29 transactions per second and compiles all of the data into a single platform for statistical modeling and predictive analysis, enabling an omnichannel approach that tailors customer experiences.
  • A large bank like JPMorgan Chase and Co generates enormous amounts of data, and it uses Big Data technologies like Hadoop to process this information. An analysis of Big Data enables banks to provide their customers with reports on customer trends, conduct individual investigations, and generate quick reports.

2. In Education

Students, faculty, courses, and results generate enormous amounts of data in the education industry, which can be used to generate useful insights for improving how educational institutions operate and function.

Big Data plays an important role in this sector, from boosting effective learning, enhancing international recruitment for universities, helping students set career goals, reducing university dropouts, allowing for precise student decision-making is enhanced as are student outcomes as a result of better evaluation and decision-making.

  • The University of Florida serves as an excellent illustration of this point. Data extraction, loading, and transfer are handled by IBM InfoSphere, IBM SPSS Modeler, and IBM Cognos Analytics for analyzing and predicting student performance at the university.
  • The likelihood of students dropping out of school can be estimated using a variety of factors, including their grades, backgrounds, demographics, and socioeconomic status. Students who are on the verge of dropping out of school can be helped by this information.
  • Big data services can also be provided to educational institutions by companies in our network. Panorama Education is a good illustration of this type of business. Teachers, students, parents, and staff can use this platform to better communicate with one another and with school districts and administrators, as well as to improve student learning skills and progress.
  • Students' attendance, behavior in the classroom, academic performance, and social-emotional learning can all be assessed using the platform's data. It provides insights that help educators identify at-risk students at an early stage and provide assistance to students in the areas they need most.

3. In Media

Traditional media consumption methods are losing their luster as newer methods of consuming content online via gadgets take over. As a result of the massive amounts of data generated, big data has made headway in the industry.

There are many ways in which predictive analytics can be used to help businesses understand their customers and their preferences, including what genre, music, and content they prefer, how many customers are churned each month, and how to optimize their media streaming schedules so that they can be more effective in terms of time and cost.

  • Netflix is a great example of how big data has helped to transform the media industry. The platform's technology affects both the shows it invests in and the way they are delivered to their subscribers. Everything from the customized thumbnails to the contents we see in the "Popular on Netflix" section is affected by the user's viewing history, including the points where they have paused the video for any particular show.
  • Viacom18 is yet another powerful example. As part of its ongoing research into emerging technologies, the company has built a big data platform on top of Microsoft Azure.
  • Using big data analytics, the platform has been able to keep viewers engaged even during commercial breaks, generating significant revenue for both the platform and its advertisers. This has been made possible by pinpointing the optimal times for commercial breaks.

4. In Healthcare

In modern healthcare, Big Data plays an important role. With its ability to decrease treatment costs, foretell epidemics, avoid preventable diseases, improve overall life quality, and predict the daily income gained by patients to arrange staffing, as well as use Electronic Health Records (EHRs), implement real-time alert systems to facilitate immediate care, adopt health data for more effective strategic planning and reduce fraudulent activity, technology has revolutionized the healthcare industry.. Read more..

  • Mayo Clinic is a credible example of the use of Big Data in healthcare. Patients with multiple conditions can be identified and their quality of life improved using the platform's big data analytics. Additionally, this analytics can identify at-risk patients and provide them with greater health control and basic medical intervention..
  • MedAware is yet another good example. If you're looking for an Israeli startup that's trying to combat the disturbing trend of detecting errors before they happen, this is the company for you.

5. n Agriculture

As a result of big data analytics, smart farming and precision agriculture operations save money and open up new business opportunities in the agriculture industry.

In order to meet the growing demand for food, big data can be used to provide farmers with timely and accurate information about changes in rainfall, weather, and other factors that affect crop yield. It can also be used to help farmers make informed decisions about pesticide use, manage farm equipment, ensure supply chain efficiency, and plan when, where, and how to plant seeds and apply pesticides.

  • Machine learning and artificial intelligence (AI) have been used to create a weed identification app developed by Bayer Digital Farming, a Bayer Group subsidiary.
  • Farmers use the app to take pictures of weeds, which are then compared to a database of around 100,000 photos maintained by Bayer to determine the species. Using this app, crops are protected and yields are increased.
  • Its customers can get agricultural information and market intelligence from a Schneider Electric division called Digital Transmission Network (DTN). Farms and commodity traders can monitor weather and market conditions via DTN to better manage their businesses.

6. In Travel

Big Data has played a significant role in improving transportation.

Big Data has had a significant impact on this industry, whether it's helping to manage revenue, managing reputation, conducting more strategic marketing, conducting advanced market research, or conducting targeted marketing.

Google Maps, for example, uses big data to plan out routes that are tailored to the needs of users, reducing wait times, identifying congestion hot spots, and even identifying accident hot spots in order to improve traffic safety and efficiency.

  • Uber is a good example of how Big Data is being used effectively in this industry. All of the data generated by the platform is used to predict the demand and supply of drivers, as well as established trip fares, based on a massive amount of information.
  • Another example is Hipmunk, a travel booking startup that uses data from airlines, customer profiles, social graphs, and reviews to tailor search results to meet the needs of individual customers and speed up the flight booking process. The platform examines all of the available data to provide customers with exactly what they need when it comes to booking travel accommodations, rather than requiring customers to discover these on their own.

7. In Manufacturing

Manufacturing is no longer a physically taxing process. The manufacturing process has been completely transformed by the use of data analytics and cutting-edge technology. When it comes to improving manufacturing, customizing product design, assuring proper quality control and overseeing the supply chain, Big Data has proven to be an invaluable tool.

  • Rolls Royce is an intriguing example of how big data is being used in this industry. Through Big data analytics, Rolls Royce is streamlining its product development process while also enhancing product performance and quality while also reducing costs. By eliminating design flaws, the platform was able to streamline its production processes even further.
  • BMW is yet another manufacturing company that is using Big Data to its advantage. Toward the development of self-driving cars, BMW uses big data for predictive analytics. In order to achieve this, the platform has collaborated with Intel on artificial intelligence. Mobileye's computer vision technology can now be used by BMW, thanks to Intel's acquisition of Mobileye.

8. In Government

There is a massive amount of data that governments have to deal with every day, no matter what country they're in. In part, this is due to the extensive updates they have to keep on the various records and databases of their citizens, as well as their growth, geographical surveys, energy resources, and so on. The government will be able to use this information to its advantage if it is thoroughly examined and studied.

This data is primarily used by the government for two purposes: welfare programs and cybersecurity.

As part of Welfare Schemes and other government programs, data is used to make faster and more accurate decisions in the area of political programs, to identify areas that need attention, to keep track of agricultural fields, and to overcome national challenges like terrorism, joblessness or poverty.

For example, fraud detection and tax evasion are two common uses of analytics in the field of cyber security.

  • The Department of Homeland Security is a good example of how the federal government is utilizing Big Data (DHS). The Department of Homeland Security (DHS) uses an intrusion identifying system for sensors to protect its systems from malware and unauthorized access in addition to monitoring internet traffic entering and leaving federal networks.
  • Data from space-based sensors, land, and the sea are collected by the National Oceanic and Atmospheric Administration (NOAA). The platform gathers and examines large amounts of data using a big data approach in order to arrive at the correct conclusion.

9. In Retail

Using big data in retail can help retailers anticipate new trends, find the right customers at the right time, lower marketing costs, and improve the quality of customer service.

When it comes to retail, Big Data can be used for a wide range of purposes, from keeping an eye on every customer and making it easier to engage with them, to optimizing pricing to capitalize on new trends and streamlining back-office operations, to improving customer service.

  • One of Canada's largest shoe and accessory retailers, Aldo, uses big data to stay afloat during events like Black Friday. In order to provide a flawless eCommerce experience, the platform uses a service-oriented big data architecture that integrates multiple data sources related to payment, billing, and fraud detection.
  • Amazon uses customer data to build a recommendation engine based on customer preferences. It's easier to persuade a user to buy something if the platform has more information about what that user wants to buy, and knowing that gives it the ability to simplify the process and persuade them to buy it.

Collaborative filtering is the platform's recommendation technology, which means it creates an image of the user and offers products that people with similar profiles have purchased.

10. In Energy and Utilities

Smart meters, grid equipment, weather data, power system measurements, storm data, and GIS data are just some of the sources of Big Data used by energy and utility platforms. In order to reduce costs, improve operational efficiency, reduce carbon emissions, and handle increased energy demand from customers, these platforms use this data.

  • In the energy and utilities industry, Google's Superstorm Sandy Crisis Map is a good example of how Big Data can be used to make money. Data from multiple sources, including satellite imagery and video feeds, as well as information about evacuation routes, emergency facilities, and traffic patterns are all included in the map.
  • Direct Relief International, a non-profit organization that provides medical aid to those affected by civil arrest, poverty, and natural disasters both in the United States and around the world, is another effective example.

A partnership between the platform and Palantir Technologies was formed in order to identify vulnerable populations exposed to the storm, assess potential emergency situations, and locate medical clinics in flood-prone areas in order to ensure that medical aid and supplies can be properly distributed to those who need them and integrate and examine various datasets such as shelter locations and almost real-time epidemiological alerts from the Red Cross and G

11. n Food industry

You may be wondering how Big Data is used in the food industry. Firms benefit from the use of big data in their marketing campaigns, as well as the ability to keep track of their competitors' growth rates, control quality, and examine purchasing and pricing decisions...

For example, by determining whether ingredients have been substituted or measurements have been altered (or both), this data assists owners in monitoring quality-related factors like product quality and uncovering underlying causes such as seasonality and storage-method variations.

  • Using Looker's big data analytics platform, Blue Apron, a fresh ingredient and recipe delivery service, has been able to reduce the time it takes to make food delivery decisions by up to one day.
  • Starbucks is yet another good example. Starbucks uses the information it gathers from its mobile payment app users to track customer preferences, such as individual likes and dislikes, which are then used to develop relevant marketing messages, such as an offer designed to entice a customer who hasn't been to the store in a while.

These are just a few of the many practical uses for Big Data, which is already making an impact across a wide range of industries. It's my sincere hope that this post has shed some light on how Big Data can be used in the previously mentioned fields.


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