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Editor's note: Big data is undoubtedly one of the hottest topics in the past few years, and the development of the Internet has made the acquisition of information and data simple and fast. So far, big data is still mainly used in large enterprises, but it is undeniable that big data is also increasingly important in small and medium-sized enterprises. So how can small and medium-sized enterprises seize the trend of big data and use it to realize the development of the company?
Data management through big data technology and related tools is the **** same topic at the enterprise and national level. Currently big data technology is mainly used in large enterprises, although more and more small and medium-sized businesses are gradually getting on board with the use of big data.
It is expected that by 2025, big data analytics and management will no longer be the preserve of large enterprises. In the coming years, big data technologies will continue to aid production and optimize internal processes.
What lessons can we learn from industries that are already practicing this technology in their workflows? First, let's take a look at some success stories of big data applications.
Big data as a new driver of business growth
The amount of information generated in the age of digital technology and social networking has grown exponentially. If a company has a website and an app, it also has data that can be analyzed at the same time. But how does it help a business?
Some large organizations started thinking about this seven years ago, and even so, only 17 percent of companies worldwide used big data in their operations in 2015. It's no surprise that IT companies, banks and telecoms firms have proved to be early practitioners of big data, as these sectors have long amassed huge databases. Banks accumulate data through transactions; telecom companies get data through geolocation information; and search engines use users' histories to get data.
In the U.S., big data is already being used in a wide range of industries, though the demand for the technology is still relatively low in Europe and Asia.
Over the past five years, organizations have tripled their use of big data, and this growth trend is set to continue, with Statista predicting that the global big data market will reach $103 billion by 2027, twice as much as it was in 2020.
Big Data Trends, Preferences and Implications Across Industries
Companies that ignore big data technology may face a loss of profits, which is why there is a growing interest in it. For example, Caterpillar, a leading manufacturer of professional equipment, admitted that its distributors lost about $15 billion simply because they did not implement big data technology.Caterpillar equipped its more than 3.5 million vehicles with sensors for operating condition data collection, and that data helps owners optimize the use of equipment and maintain cost management.
Loss of profit is often seen as a loss of customers and a lack of optimization. With organizations now focusing on developing in-house big data expertise, it's clear that it's everyone's **** to grasp the impact of big data on company processes.
Investment in big data analytics is also on the rise. In fact, over the next few years, companies that have already adopted big data analytics will continue to grow the number of big data projects.
Spending on big data analytics depends on the industry sector. For example, the use of this technology is costing telecom companies millions of dollars because they need to use more and more servers to store and process data and use it to aid in protecting confidential data.
Big data solutions for organizations vary depending on the type of data being collected and the challenges being addressed, so let's look at some great examples.
1. Big data in e-commerce
Before the advent of personalization, marketers generally relied on market research and sales analytics to get a handle on customer needs. However, there was still a big discrepancy between the results obtained through this method and the reality.
In 2018, HM's profits fell for the tenth consecutive quarter, seriously threatening the company's survival. The company later used big data algorithms to stabilize the situation, emptying 40 percent of its inventory without reducing sales.
Photo credit: Pexels
Retailers have access to a wealth of data that can be used to communicate with customers and optimize internal processes. The big data technology used by Walmart.com requires processing 2.5pb of data every hour.
Modern retail is moving from CRM marketing to predictive analytics.
2. Big Data in Healthcare
Medical data analytics has huge potential. With the application of big data technologies in healthcare, this sector will likely benefit from the following:
_Lower processing costs;
_Predicting epidemics;
_Providing early screening for diseases;
_Improving overall quality of life;
_Applying modern treatments to practice.
As the largest independent pharmacy profit management company in the United States and one of the largest pharmacies, ExpressScripts processes millions of prescriptions each year from home delivery and retail pharmacies. This data contains a wealth of patient information, so medical professionals can learn about the side effects of medications well in advance of prescribing them to patients.
And this will benefit a major improvement in the NHS::
Healthcare providers will determine whether a patient is at risk of addiction before prescribing them painkillers. Under these conditions, healthcare providers can choose different treatment options and also monitor the patient's drug use more closely.
Analysis of prescriptions, physiology, and other medical information will help identify chronic conditions or diseases that have not yet been adequately diagnosed for research;
Analysis of a patient's adherence to medical orders after discharge from the hospital will help to predict the likelihood of readmission within the next 90 days and assist in taking appropriate measures to prevent readmission.
3. Telecom Big Data
Telecom companies offer telecom solutions that attract many subscribers every day, but this also provides opportunities for telecom fraud. Illegal access, illegal authorization, falsified data, cloning, and behavioral fraud are the most common types of fraud. In addition, fraud has a direct impact on user favorability. Therefore, systems, tools, and methods for detecting fraud are widely used in the telecom field.
China Mobile, the world's largest mobile operator in terms of subscribers, has developed Tianshield encryption software based on big data analytics and machine learning technology. The developers used a database of fraud cases provided by the police to train an algorithm that enables it to detect typical telecom fraud content and block spam and phone calls.
The system can also identify groups of users who send frequent spam and send them warnings. In addition, China Mobile said, "The accuracy of SkyShield will also continue to improve as it is put to use.
Image credit: Pexels
4. The Big Data Potential of Web Application Development
Big data can optimize a company's internal processes by implementing and integrating it into an organization's existing mobile and web applications. For example, UPS Logistics, the foremost supply chain management company in the U.S., ships more than 16.9 million shipments to more than 220 countries every day, and this could not be done without the solutions provided by Big Data.
To optimize routes and reduce costs, UPS uses the Orion application, which stands for On-roadIntegratedOptimizationandNavigation, or integrated road optimization and navigation. The application, which serves as the company's fleet management web application, uses a large amount of map data, data on departure and arrival points, shipment dimensions and shipment delivery times to generate optimal routes.
As a result, UPS saves about 6 million liters of fuel, reduces carbon emissions by 13,000 tons and improves delivery speeds every year.
5. Big Data in Education
A leader in U.S. enterprise and education programs, Skillsoft has partnered with IBM to leverage internal data on user interactions to personalize their user experience, increase engagement, and improve learning outcomes, both directly through projects and through email communications.
They utilize data on user activity to monitor user engagement and determine the best communication channels and timing of communication to capture user attention. In addition, based on user preferences, they build educational content recommendation systems. In addition, the company has customized data-based visualization tools for each user.
6. The Advantages of Big Data for Marketing
To track and predict shopping behavior, BikeBerry, an online bike and motorcycle retailer, employs sophisticated machine-learning algorithms and statistical models to collect data on users' purchasing histories, demographics, and behavioral information, which, combined with the company's other technologies, help them to their site's user behavioral patterns are recognized and applied.
As a result, the store was always able to recommend the most relevant products to their customers and began to offer targeted discount offers to those who actually needed them, and in the end:
Their sales grew by 133%;
their user activity increased by 200%;
the number of repeat customers doubled;
this category of customers have seen a 30% increase in their average bill amount.
7. Big Data in Transportation
Union Pacific Railroad, the largest railroad in the U.S., is already using big data to enhance its risk-management system, resulting in a 75 percent reduction in train derailments. The company collects data from each train's thermometers, auditory and visual sensors, information on weather conditions, the status of the braking system, and the train's GPS location.
Based on this data, Union Pacific is able to generate predictive models that can monitor the condition of wheels and railroads and predict train derailments days or even weeks before an accident.
Big data technology makes it possible to deal with such problems quickly, avoiding damage and delays to trains.
Image credit: Pexels
8. Big data applications in public ****administration
Governments use big data analytics to aid in decision-making in areas such as healthcare, employment, economic regulation, crime and security, and emergency response.
Using big data solutions, the Los Angeles Police Department can access the conditions and areas where crimes of all types most commonly occur and dispatch additional officers for prevention. The LAPD's system utilizes historical data on the time, type, and area of crimes and then processes them with spatial and temporal clustering algorithms.
No personal data of the city's residents or their location data was used in this case, in compliance with privacy regulations. In addition, the reduction in crime saves money 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 promising future in conservative industries such as agriculture, as big data can help such industries save labor and resources.
With global demand for food expected to nearly double by 2050, farmers are under immense pressure to increase production. In this context, big data can assist farmers in managing seeds, fertilizers and pesticides by synthesizing and analyzing information received from soil sensors, tractors with GPS trackers and local weather channels. More importantly, it helps increase productivity.
10.Benefits of Big Data for the Mining Industry
In the mining sector, where companies are facing increasing competition due to increased demands on the environmental component of production, it has become critical to use resources as sparingly as possible.
Mining giant Severstal has applied a system based on the Internet of Things and big data analytics to monitor electricity consumption. The company says the solution significantly improves the quality of energy consumption forecasts, and by reducing fines, optimizing purchases, and combating power theft, they can save $10 million a year.
Conclusion
Businesses have been embracing big data for some time now, and the flow of data has never been more intense. Today's social networks, online services and apps can all be interconnected, and businesses can get a more complete picture of their potential customers as a result.
Many have called big data the "new gold. Data analysts predict that big data will soon become a major decision-making tool for all businesses. Small startups and large international companies alike can benefit from this technology.
Translated by Buckle Up