In the age of big data, companies collect users’ information at an ever-increasing rate. However, traditional methods cannot efficiently process or analyze these huge datasets. The challenge lies in taking huge volumes of data and turning it into something usable, like marketing campaigns. Having big data examples to reference can be a big help.
So, what is big data, and how can you leverage it for your career development or business? These real-world examples of big data can help you achieve your business goals. A large part of business success is using big data for advanced analytics and predictive modeling. If a business can predict beforehand if something will sell or flop, it can save a lot of time and money.
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What Is Big Data?
Big data refers to oversized or complex information that cannot be processed efficiently using regular tools or software. The information designated as big data depends on the available capabilities, organizations, and tools. Generally, big data refers to how massive amounts of information can be analyzed or managed in order to generate significant insights or ideas.
The process of customer analytics uses big data to track a customer’s digital footprint. This allows businesses on social media sites or Google to create ads that the customer is more likely to engage with. Since big data continues to grow and evolve, professionals in this field utilize the five Vs to define its features. The five Vs are volume, variety, veracity, velocity, and value.
Where Is Big Data Used?
- Hospitality industry
- Entertainment industry
- Education facilities like universities
- Healthcare organizations
Why Is Big Data Important?
Big data helps companies accomplish incredible results. Using big data streamlines resource management, generates higher revenue, and helps businesses make sound decisions. Hence, big data is an essential key feature in executing business tasks.
Some examples of important tasks that derive from big data are identifying the different causes of failure or defects in real time, identifying anomalies faster, detecting unusual behaviors before they become fraud incidents, and classifying and reacting to variables.
Real-World Examples of Big Data
Big data is essential in the healthcare sector and government agencies such as NASA. It facilitates data collection, tracking, and execution of other fundamental tasks, helping run organizations smoothly. Below are some global companies and government bodies that leverage huge amounts of data to accomplish incredible results.
10 Great Examples of Big Data
Big Data Example 1: Amazon
Amazon is a record-setting top e-commerce shop, thanks to its database. The company utilizes an advanced approach to big data to enhance customer experience, accomplishing massive annual sales. Users’ purchases, frequency of online activity, and product reviews are all collected in huge quantities.
Amazon gets customer feedback through this data, leveraging predictive analytics to target its marketing efforts to prospective buyers. A company can streamline the shopping experience by taking into account fine details such as what a customer wants to buy. There is such a massive volume of searches because of Amazon’s app for mobile devices that Amazon is probably the best example of big data.
Big Data Example 2: DIBELS
The education industry is utilizing big data to improve teaching methods. San Francisco’s Roosevelt Elementary School instructors use DIBELS, an analytics application, to ensure effective teaching. This app helps teachers identify whether their students need professional assistance based on their reading habits.
Once they identify their students’ learning needs, they can group them according to the specific issues. Suppose a teacher identifies the same problem across many learners; they can adjust their teaching methods to facilitate effective learning.
Big Data Example 3: GE
The airline industry is leveraging vast amounts of data to ensure optimum performance. GE flight efficiency service is among the top applications of big data in airlines across the globe, including Southwest Airlines. The service maximizes fuel use and safety by assessing airplanes’ huge amounts of data.
Typically, a transatlantic flight will generate an average of 1,000 gigabytes. GE has solved one of the biggest industry-specific big data challenges by figuring out a way to process these massive amounts of data, including data on fuel efficiency, passengers, weather conditions, and cargo weights.
Big Data Example 4: McDonald’s
Like other businesses in the food industry, McDonald’s has faced numerous challenges regardless of its consistent expansion. Due to the different changes and trends, McDonald’s analyzes huge amounts of data gathered in the past.
For instance, when consumers started buying into the idea of healthy living, as a fast-food restaurant, McDonald’s had to address this problem. Thanks to big data, the restaurant learned customer behavior and provided digital menus, mobile apps, and drive-thru experiences, allowing its customers to pick healthier versions of its food.
Big Data Example 5: NASA
Space agencies collect a large amount of data from satellite probes in outer space and orbiting the earth and other planets. Before launching a rocket, these agencies must perform multiple calculations and assess data while considering factors such as orbit location, payload, trajectory, and time.
Therefore, they analyze petabytes of data, simulate the flight path, and then launch the actual payload. NASA is another example of an organization that has solved major analytical challenges. It utilizes big data to analyze and manage data to run simulations. This helps launches to be more efficient and safe.
Big Data Example 6: Netflix
With over 150 million subscribers, Netflix gathers large amounts of data that is difficult to process with traditional methods. Big data allows the company to track what their clients watch, when the show is paused, the scenes watched twice or more, how fast they finish a series, and the device they use. There are even larger amounts of data now that Netflix has an app for your phone.
Consequently, the online platform offers a great customer experience, recommending shows and movies accurately. That’s why the company boasts a high customer retention rate. You may be wondering how the company decides to invest insurmountable amounts of cash in a show, but big data helps them settle on profitable deals and decide which shows would be the most profitable.
Big Data Example 7: Salesforce
Massive datasets pose numerous challenges. That’s why most companies prefer to spread information on different platforms. However, Salesforce operates under cohesion principles and therefore deals with huge amounts of data. Customer relationship management combines information from different departments, including sales and marketing.
It provides artificial intelligence-driven insights and accurate sales and customer churn projections. It also enables users to connect to external data management products easily.
Big Data Example 8: Splunk
The rise of big data has led to increased cyber attacks. This is due to the fact that the more data you store, the more vulnerabilities you have, leading to data breaches. According to Statista, 156 million consumer records experienced security threats in 2020. This was double the number of cases found in the previous year.
Splunk’s security operations utilize big data to detect and address fraud and cyber security issues. Splunk’s tools process the entire system’s data, identifying anomalies through machine learning algorithms. Its data-driven insights allow companies to map out multipart attacks, prioritize security breaches, and determine the causes of security issues.
Big Data Example 9: Tempus
Tempus leverages big data to make medical records accessible and portable. The company trawls massive amounts of electronic health records to provide data-driven treatments. According to CMS, Americans spend trillions of dollars annually on healthcare. However, patients and doctors don’t enjoy a robust, long-term relationship, which is necessary for effective treatment.
Instead, they are more connected to wearable devices such as the Apple Watch, which monitors the heart rate, and Alphabet’s in-built skin temperature monitor. Compared to doctors, these wearable devices can gather data over a prolonged period rather than during appointments, using healthcare data analytics to make accurate diagnoses and predict where healthcare is needed the most.
Big Data Example 10: Uber
Predictive analytics is used by this rideshare company to project demand and driver availability. Hence, the company can plan for the number of rides required, provide incentives to its drivers, and set the right prices.
Data analysis also helps the company to accomplish customer satisfaction. No wonder the company was able to expand its services to Uber Eats and deliver food. Moreover, this giant rideshare company continues to realize large profit margins regardless of the competition in the industry.
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Pro Tips to Boost Your Big Data Skills
- Apply machine learning to big data. With business intelligence, past aggregates matter. Machine learning helps interpolate and extrapolate previous experiences to deal with future situations. If you’re interested in learning machine learning, big data is a great area in which to use those skills.
- Leverage technology. Technology continues to improve in almost all sectors, and big data is no exception. You can gather, store, and secure vast amounts of data using new technologies. Moreover, it allows you to analyze data accurately, developing an effective business strategy.
- Earn a Master’s Degree in Big Data Analytics. Becoming an expert in a specific field demands mastery of the elements involved. A Master’s Degree in Big Data Analytics can help you acquire essential knowledge and skills, making you an expert in big data analysis.
What Should Be the Next Step in My Big Data Learning Journey?
Businesses are achieving high-profit margins as a result of big data. As a business owner, you can leverage huge datasets to improve your company’s performance and productivity, obtaining enormous profits.
Whether you’re in the private sector or the public sector, you can accomplish exceptional business growth. All you need is the right tools to help you process huge amounts of data efficiently.
Big Data Examples FAQ
The four types of big data analytics include predictive analytics, descriptive analytics, diagnostic analytics, and prescriptive analytics.
The US Department of Education uses big data to analyze learning programs and see when students are falling behind or getting bored and can then adjust programs accordingly. Some agencies can find themselves in difficult situations because of this. For instance, when police departments apply predictive policies in identifying perpetrators and locations of crime, they often get accused of privacy violations.
For effective analysis of big data, unstructured data must be transformed into structured data.
Yes, big data is significant in the operation of banks. Due to the increase in data in the banking sector, organizations are utilizing big data to identify illegal activities such as money laundering and misuse of debit or credit cards.
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