The digital revolution paved the way for bigger digital footprints. And while the vast array of data points making up our digital activities may seem impossible to define, the truth is that everything can be quantified and tracked.
Information collected by companies on their customers, online searches, and data gathered by applications or wearables are just some of the big data examples processed by governments and tech giants. Big data has improved efficiency by transforming how businesses operate and use information to develop new products and services. Perhaps unsurprisingly, there is a growing need for IT experts in big data analytics. Keep reading to learn more about the multiple examples and applications for big data.
Examples of Big Data
Almost every aspect of our lives revolves around technology and using digital devices that make information more accessible and help us stay connected. These modern gadgets produce a huge volume of data that affect a variety of industries:
- Government sector
- Media and entertainment
- Banking and financial services
Big Data Applications in Cybersecurity
The cybersecurity industry is one of the most significant users of big data and its applications. Cybercriminals are constantly trying to find ways to exploit vulnerabilities in systems or break into networks. The best way to address these security issues and ensure protection against these attacks is by using technology that allows for a quick analysis of huge amounts of information.
Another important component is intrusion detection. With this type of system, a company is notified when someone tries to access their network without authorization and prevents them from gaining entry into sensitive areas within an organization's computer systems. This benefits both parties because it allows legitimate users easy access while keeping out the bad guys.
In order to effectively combat cyberattacks, it is essential for organizations to use all the tools at their disposal, and big data is one of the most powerful weapons in their arsenal. By analyzing various intrusions, data theft, and applying machine learning, they can better understand how cyber-criminals operate and develop strategies to thwart their efforts.
Big Data Examples in Healthcare
The healthcare industry is another industry benefiting from big data applications. Medical professionals use analytics to better understand their patients' needs, predict future illnesses within populations, and identify those at risk for specific diseases. This leads us into personalized medicine, where each person receives treatment tailored specifically for them, increasing the chances of a successful outcome.
Another big data application in healthcare is diagnostics. With the ever-growing volume of medical data available, it is now possible to detect diseases at an early stage when they are more treatable. This also allows doctors to monitor patients more closely and identify any changes in their condition that might require attention.
Big data is also being used to improve the overall quality of healthcare. By analyzing data from electronic health records or EHRs, hospitals and clinics can see how well their treatments work and identify areas that need improvement. In addition, they can compare the results with those of other organizations to find out what works best for them.
Furthermore, with the development of wearables, large amounts of sensors scan data for each patient. Like Apple’s HealthKit, some companies developed a way for users to store their real-time sensor data and create health records on their phones.
Government Technology and Big Data
Governments have been using big data for many years to help them make better-informed decisions. One of the most notable examples is the Obama administration's use of analytics in its healthcare reform initiative. The team used data from insurance companies, hospitals, and other sources to create models that showed how different changes would affect the system.
Big data is also being used to overcome specific challenges such as unemployment and terrorism. Depending on how social media and other sources process big data, governments can better understand the factors contributing to these problems and develop strategies to address them.
Smart cities benefit greatly from big data maps. With this technology, city officials can use sensors to collect data on everything from traffic patterns to air quality. This information can then be used to make decisions about things like where to place a new bridge or build a road.
Big data is also being used in agriculture, energy, and many other critical sectors.
Example of Big Data in Meteorology
One of the most common applications for big data is in meteorology. Weather forecasting agencies like the National Weather Service use it to create models that predict weather patterns up to a week in advance. These models are based on environmental data collected from satellites and other sources, including weather stations, radars, and balloons all over the world.
Big data is also used to monitor weather conditions in real-time. This information is then used to issue warnings about severe weather events, such as tornadoes and hurricanes.
Big Data Application Examples in Media and Entertainment
The media and entertainment industry is another area where big data is used to great effect. For example, Netflix uses analytics to decide which shows to produce and how to market them. They also use it to determine what kind of ads to show viewers.
Big data is also an important part of Twitter’s success. By analyzing the tweets people send out, they can determine what's trending and show relevant ads to users based on those trends.
Big Data Examples for Transportation
One of the most important applications of big data is in transportation. By collecting and analyzing data from sensors on vehicles and public transportation systems, engineers can improve traffic flow and shorten commute times.
Big data is also being used to make buses and trains more efficient. By tracking where passengers are getting on and off, transit officials can plan routes that serve more people.
Marketing and Big Data
The bulk of the work by big data companies revolves around marketing. Modern marketing relies on the collection and analysis of customer data, which is used by companies to determine what products to produce and how to market them. The most effective marketing channels are then used to reach the target audience.
One of the heavyweights that relies on big data for its marketing efforts is Amazon. The company uses analytics to determine what items are being searched for the most and what other products are popular with consumers. They also use big data in their marketing campaigns and even track the locations of customers via GPS devices so they can send targeted ads straight to people's smartphones.
Education and Big Data
Big data is also being applied in education. By collecting and analyzing performance data, teachers can identify the most effective type of teaching methods for individual students.
By analyzing data about the skills and interests of students, big data can be used to predict their future career paths. This information helps students make more informed decisions about their education and future job prospects.
By tracking a student's progress over time, big data can be used to create customized learning programs that enhance learning efficiency. This is especially helpful for students who are struggling in certain subjects or who are already interested in a certain career.
Big Data for Banking and Financial Services
The banking and financial services industry relies heavily on big data analysis. Banks use analytics to improve credit scoring models. The scores are then used as part of the risk assessment process for loans.
Transactions data can be used to analyze customers' spending habits in order to offer more relevant products and services.
Other companies use massive data sets to analyze the stock market and predict which stocks will perform to ensure better investments for clients. This information can then be used by investors to determine what assets to buy or sell.
What Is Big Data?
Big data is a mixture of structured, semistructured, and unstructured data accumulated by organizations in large volumes. The scope of the gathered information is so vast that conventional data management tools aren't able to process, store, and analyze big data.
Big data structures are excellent for mining information, machine learning projects, predictive modeling, and other advanced data analysis applications. It offers valuable insights into everything from shopping habits to health care.
Some of the most interesting statistics on big data reveal the staggering amount of data sets that we generate daily.
Types of Big Data According to Structure
Structured data is the most common type of big data and usually resides in tables. The table has a specific format with columns and rows, making it easy to understand and use for analysis.
Unstructured data is the most difficult to work with and doesn't follow any specific format. It can be text, images, or videos, making it hard to process and use for analysis. These raw formats of big data are the most difficult to manage and often require significant work to extract any real value.
One of the best examples of unstructured data is the search result you get from Google. The search engine will draw text, videos, and images from its database of indexed websites for the term you searched.
The V’s of Big Data
In addition to outlining big data examples, it's important to name the key characteristics. These were defined in 2001 by Doug Laney and popularized by Gartner, Inc. They are referred to as the three V’s: volume, variety, and velocity. The list was later expanded to include value and veracity.
Volume is the first characteristic of big data and describes its size. The term refers to the amount of data being generated, and it’s one of the most essential characteristics. For most organizations, it grows exponentially and may vary from several terabytes to hundreds of petabytes.
Variety refers to a diversity of sources (structured, unstructured, or semi-structured). This characteristic represents one of the main advantages of big data analytics and examples where data derived from photos, videos, emails, GPS location data, and audio is processed to get valuable information.
The velocity of big data refers to the time it takes for data to be generated, collected, and analyzed. The faster the data can be processed, the more value it has.
This characteristic is closely related to the other V’s, but it describes how big data is analyzed and used by decision-making. The value can be seen in the real-time analysis of information, more effective procedures, better relationships with customers, and other easy-to-quantify benefits for businesses.
The last data characteristic refers to quality and accuracy. It’s important to know that you’re analyzing useful and relevant data for making decisions.
Relevance of Big Data
There are many uses of big data, and great companies use it to improve operational efficiency, customer satisfaction, their marketing strategy, and any other action that can help grow profits. As such, big data is an important tool in giving companies the edge over the competition.
Some of the most common big data examples are:
- Using customer data and purchase histories to recommend similar or complementary products
- Predicting how much inventory a company will need and when items will run out is straightforward with product sales data
- Analyzing social media posts to understand public sentiment about a product or service
- Tracking website visits to better understand consumer behavior
- Forecasting demand for products and services
- Detecting fraudulent activities
- Predicting trends with consumer data
Big data has become an essential part of business. It’s a must-have for companies that want to succeed in the digital age. The advantages it brings are vast and varied, making it an important tool for different organizations.
There is no shortage of examples of companies using big data to improve their performance and, by extension, their bottom line. With technology becoming more advanced, there is a growing number of sources emerging, and big data is evolving. Dedicated professionals are now needed to get the most from the increasing volume of information.
Data is essential for any organization today as it allows them to make informed decisions about their products and services based on real-time information that has been gathered from multiple sources. The importance of enterprise-scale data can’t be understated because, without it, businesses wouldn't know what their existing customers are saying about them and how they can improve and follow the latest marketing trends.