Big Data Technology Success Cases and Trends 2021-25
Big Data Technology Success Cases and Trends 2021-25
Data management through Big Data technology and tools is a relevant topic at the enterprise and state levels. Today, mainly large enterprises use Big Data technology today (about 60% of the market). However, the number of medium and small businesses infusing this tech is growing each year.
By 2025, Big Data analysis and management will no longer be the prerogative of large companies only. In the coming years, Big Data technology will continue to help work more effectively and optimize internal processes.
What can you learn from those already implementing the technology in workflows? First, let’s see some of the bright Big Data success stories.
Big Data as a New Business Development Driver
The amount of information generated in the era of digital technologies and social networks is growing exponentially. If a company has a website and an app, it already has data that can be analyzed. But how can it help the business?
Large companies started to ask this question 7 years ago. However, only about 17% of companies worldwide employed Big Data in their operations in 2015. IT firms, banks, and telecommunications companies have turned out to be the early adopters of Big Data. However, it’s no surprise. These sectors accumulate the most significant amount of data. Banks accumulate data through transactions; telecoms get data through geodata, search engines use query histories.
In the United States, a wide range of industries is using Big Data. Meanwhile, in Europe and Asia, the demand for this technology is slightly lower.
Businesses have started using Big Data three times more in the last five years. Moreover, the application is going to grow. Statista predicts that the global Big Data market will reach $ 103 billion by 2027, doubling what it was in 2020.
Big Data Trends, Tendencies, and Impact Across Industries
Companies that ignore Big Data technology risk losing profits. Therefore, this fact explains the growing interest in this tech. For example, Caterpillar, a leading specialized equipment manufacturer, admitted that its distributors lost about $ 15 billion simply because they didn’t implement Big Data technologies. To illustrate, Caterpillar has over 3.5 million vehicles equipped with sensors that collect data on operating conditions. This data assists owners in optimizing the use of their equipment and managing maintenance costs.
Lost profits often manifest in the form of lost customers or missed optimization. Today businesses are focusing on the development of internal Big Data expertise. Hence, a good understanding of Big Data’s impact on processes goes by default.
Investments in Big Data analysis are increasing. Indeed, companies that already employ Big Data analytics will not stop growing the number of their Big Data projects over the following years.
Spendings on Big Data analytics depend on the industry domain. For example, the use of this technology costs millions of dollars to telecom companies. This is because telecoms use more and more servers to store and process data. Additionally, it helps to ensure data protection and confidentiality.
Big Data solutions for businesses differ based on the type of collected data and the challenges addressed. Let’s have a look at some great examples.
1. Big Data in eCommerce
Before the advent of personalization, marketers relied on surveys and sales analysis to determine customer needs. However, this method produces results that are hardly comparable to reality.
H&M suffered ten consecutive quarters of falling profit in 2018, threatening the company’s survival. Big Data algorithms were utilized to stabilize the situation, allowing for removing 40% of the store’s inventory without lowering sales.
Retailers get a massive amount of data that can be used for customer communication and the optimization of internal processes. For example, the Walmart network also uses Big Data technologies to process 2.5 petabytes of data every hour.
Modern retail is shifting away from CRM marketing and toward predictive analytics.
2. Big Data in Healthcare
Medical data analysis has enormous potential. With the use of Big Data technology in healthcare, it’s possible to:
- Lower treatment costs;
- Forecast epidemic breakouts;
- Provide early screening for diseases;
- Improve the overall quality of life;
- Introduce modern treatment methods into practice.
The largest independent manager of pharmacy benefits and one of the largest pharmacies in the United States, Express Scripts processes millions of prescriptions for home-delivered and retail pharmacies every year. Their information about individual patients has become so rich that they will soon be able to notify medical personnel of drug side effects long before it is even prescribed to a patient.
This will result in significant beneficial changes in the health system of the nation:
- Health care providers will determine if a patient is at risk of addiction before prescribing pain relievers. In such cases, it will be possible to choose a different treatment plan or more closely monitor drug consumption;
- Analysis of prescriptions, physiology, and other medical information will aid in identifying the development of a chronic illness or illness that has not yet been adequately diagnosed;
- Analyzing patient compliance with doctor’s orders after discharge will assist in predicting the likelihood of readmission over the next 90 days and take appropriate action to prevent it.
3. Big Data in Telecommunication
Telecommunication companies create solutions that attract many users every day, which makes a vast field for fraud. Illegal access, authorization, fake profiles, cloning, behavioral fraud, are the most prevalent types of fraud. In addition, fraud has a direct impact on relationships with the user. As a result, systems, tools, and methods for detecting fraud are widely employed in the telecom field.
The world’s largest mobile operator in terms of subscribers, China Mobile, has developed the Sky Shield system based on Big Data analysis and machine learning technology. It’s capable of detecting phrases typical of fraudsters, intercepting spam mailings and calls. Developers used the extensive database of fraud cases provided by the police departments to train the algorithm.
The system can also identify user groups who are particularly prone to spam and alert them. Moreover, according to China Mobile, as the Sky Shield is put into practice, the system’s accuracy improves.
4. Big Data Potential for Web Application Development
Big Data can be used to optimize the internal processes in a company through its implementation and infusion into existing corporate mobile and web applications. For example, the UPS logistics firm and the most significant supply chain management company in the US delivers more than 16.9 million goods per day to over 220 countries. It can’t do without Big Data solutions.
To optimize routes and cut costs, the company has implemented the Orion application. It stands for On-road Integrated Optimization and Navigation. The app is the firm’s fleet management web application. The system uses massive cartographic data, data on points of departure and arrival, sizes, and required delivery times of goods to generate optimal routes in real-time.
As a result, UPS saves around 6 million liters of fuel per year, cuts carbon emissions into the atmosphere by 13,000 tons per year, and speeds up deliveries.
5. Big Data Benefits for Education
An American leader in corporate, educational programs, Skillsoft, in collaboration with IBM, leveraged internal data on user interactions to tailor their experience, increase engagement, and improve learning outcomes, directly through the program and email newsletters.
The data on user activity was utilized to monitor engagement and determine the best time and channel of communication to capture the users’ attention. In addition, based on the preferences of the users, a recommendation system of educational content was built (84% of users rated the recommendations as relevant). Moreover, the company infused data-based visualization tools that tailor to each individual user in the system.
6. Advantages of Big Data for Marketing
To track and predict shopping behavior, an ecommerce store of bicycles and motorcycles, BikeBerry has implemented sophisticated machine learning algorithms and statistical models. The collected data on purchase history, demographic and behavioral information combined with the technologies the company used allowed for identifying and utilizing behavioral patterns on the BikeBerry website.
As a result, the store was able to recommend the most relevant products to customers and began making targeted discount offers exclusively to those customers who indeed required them, which helped to:
- Increase sales by 133%;
- Improve user activity by 200%;
- Double the number of returning customers;
- Increase the average check of such customers by 30%.
7. Big Data in Transport
The largest railway corporation in the US, Union Pacific Railroad, has employed Big Data to strengthen its risk management system, resulting in a 75% reduction in train derailments. The company collected data from thermometers, acoustic and visual sensors of each locomotive, information about weather conditions, the state of brake systems, and GPS location of trains.
Based on the data, Union Pacific was able to develop predictive models that allow for the monitoring of the condition of the wheels and the railway and the prediction of train derailments several days or even weeks before an incident.
Big Data technology made it possible to handle such problems swiftly, avoiding damage to trains and delays.
8. Big Data Trends in Public Administration
Governments employ Big Data analysis to make decisions in sectors such as healthcare, employment, economic regulation, crime and security, and emergency response.
Using a Big Data solution, the Los Angeles Police Department could obtain the most likely terms and areas (with great precision, about 50 square meters) of various types of crimes and dispatch additional police forces to prevent them. The LAPD’s system uses historical data on the time, type, and area of ??crime, and processes them using clustering algorithms in space and time.
No personal data of people in the city and data about their location is used in this case, which allows compliance with privacy regulations. In addition, the decline in crime has resulted in financial savings for the police, the judiciary, and the correctional system.
9. Impact of Big Data on Agriculture
Data analysts believe that Big Data has the most significant prospects in conservative industry sectors such as agriculture. This is because big data will help save both labor and resources in this industry.
Global food demand is anticipated to nearly double by 2050, putting farmers under pressure to raise output. In this case, Big Data refers to the information received from soil sensors, tractors with GPS trackers, and local meteorological channels. Comprehensive analysis of this data allows farmers to manage seeds, fertilizers, and pesticides. More, it helps increase productivity.
10. Big Data Benefits for the Mining Industry
In the mining sector, companies face increased competition due to increased requirements for the environmental component of production. As a result, the trend makes it critical for companies to use resources as sparingly as possible.
A mining giant Severstal has implemented a system based on the Internet of Things and Big Data analytics to monitor electricity consumption. According to the company, the solution can significantly improve the quality of energy consumption forecast (by 20-25% monthly) and save $ 10 million annually by reducing fines, optimizing procurement, and countering electricity theft.
Conclusion
Businesses have been using Big Data for quite a while. However, the flow of data has never been as intensive as it is now. Social networks, online services, and applications today can all be interlinked. At the same time, businesses can get the complete picture of potential customers.
Many would call Big Data the “new gold.” Data analysts predict that Big Data will soon become the primary decision-making tool for every business. Small start-ups and big international organizations will benefit greatly from using this technology.
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