Application of Big Data in Business

                                        Application of big data in business decision making

Big data is the set of structured, semi-structured, and unstructured information which are collected by a person or organization, that can be mined and used for the decision-making process. In simple words, big data is a huge and more complex data set collected from new data sources. The large volume of the data cannot be managed by traditional systems or software, but if we analyze it and manage it, it can be hugely beneficial for the business. While it is an important aspect of decision-making, Oracle (2021) said that big data are the business capital. 

As data helps businesses thrive due to innovation in the decision-making process, it is an economic factor of production in digital goods and services as well. For example, due to the lack of financial capital, a company cannot lunch a new model of vehicle in the market. Similarly, without the big data to feed the onboard algorithms, the automakers cannot make the car autonomous. Therefore, the role of data management has impacted the overall strategy of the business as well as the future of computing. 

Case study of China Eastern Airlines

China Eastern Airlines (CEA) is one of China’s three major airlines established in 1957. As a member of the SkyTeam alliance, CEA serves over 130 million passengers annually and has 1036 destinations in over 170 countries and it belongs to the top 10 airlines in the world (China Eastern Airlines, 2022). CEA has used Oracle's big data to enhance the safety of its customer, by enhancing the capacity to process and analyze the huge amount of big data from its data lab and make sure flight is safe, and reduce the operational cost. 

One of the challenges CEA was facing was promoting flight safety and getting the fuel efficiency by enabling the airline to rapidly capture and analyzed over 100TB of annual flight data record by Quick Assess Recorder (QAR) including aircraft conditions, engine life, and so on through the journey. Another challenge CEA was facing was increasing its competitive advantages by getting the high-performance big data analytics platform that supports them for marketing, customer services, and flight operation (Oracle, 2022). 

As CEA is processing and analyzing 100TB of the huge and complex data, the organization was thrilled in many ways. Firstly, CEA has integrated the thousands of sensor data from the aircraft, it has helped the organization to know the health of the aircraft such as engines, and can predict potential faults. Secondly, due to optimizing the big data analysis, has helped to get the pilot’s behavior such as actual values of flight angle, take-off speed, and landing speed. That has helped CEA to minimize the potential risk of the engine being damaged. Thirdly, due to the help of big data, CEA has maintained the record from 60 attributes, such as type of the aircraft, height, traffic, wind speed, and recommended flight speed, which has helped them to save tons of fuel each year. Last but not least, it has enhanced the customer experience as it discovers the relationship between travelers and airline service. Airline service included cabin service, baggage, marketing, website, flight operation, and so on which helped CEA to improve its quality of service. 

Application of big data

The application of big data helped businesses grow in various ways. While businesses analyzed big data, the outcome helps businesses to predict the future and perceive the solution. According to Oracle (2022), big data can be used in product development, predictive maintenance, customer experience, fraud and compliances, machine learning, operational efficiency, and driving innovation.  This paper will discuss the applicability of big data in the later chapter.

Application in production

In the production or manufacturing industry, it’s been discovered that various ways of using big data that are very beneficial for the company in a competitive marketplace. First of all, big data helps the company to reduce the west and energy cost. One of the research projects executed by Manyika et al. (2016) at McKinsey & Company reveals that one European manufacturing company used the advanced analytics system for manufacturing processes such as temperature, chemical flows, and coolant pressures and they found which factor has more impact on the overall profit. This research presented that the company manages to reduce the material by 20 percent, and cut energy by 15 percent. Secondly, with the help of big data, the company can verify the accuracy of the production. In some companies such as pharmaceutical, accuracy is very critical and big data analytics help them to make a lower errors and produce more products. At last, big data helps the organization maximize the production, company can differentiate their product to know which parts of the process go rapidly.

Application in predictive maintenance

Analysis of big data helps businesses to predict future maintenance. For example, it can be beneficial for the aircraft industry. With the help of monitoring the big data collection, it is possible to get the information for aircraft on when the parts are needed to be replaced. It increased reliability along with bolstered operational and supply chain efficiencies. These days, most industrial and electronic machines are equipped with a sensor, that can see hear and feel ever than before. It gives a huge number of data that can be analyzed, and with the help of algorithms, it can be operated in efficient ways. Daily, & Peterson (2017) believe that to know the significance of predictive maintenance and get the impactful result, machines, data, insight, and people need to be brought together. 

Application in fraud and compliances

Big data has more to do with security and compliances. Cardenas, et al. (2013) said that it has changed the landscape of security tools for network monitoring. Particularly, the banking and financial institution are relying on big data to protect the privacy of their customer and data to be leaked or attacked. For example, if you are buying something with over five thousand dollars in USD but it depends on the bank policy, the bank instantly halts the transaction and you need to call the bank to authorize the transaction. That helped the bank and customer secure if there was any fraudulent activity was involved. 

Fang & Zhang (2016) further explained that standardizing financial data from a variety of sources, reduces the response time to real-time data streams, improving the scalability of algorithms and software stacks on novel architectures. Furthermore, Banking industries have enhanced their capabilities to detect cross-channel schemes by looking at the data across various banking platforms instead of just monitoring for themselves. 


Uses of big data becomes critical for all industries. It helps businesses to stand out in the competitive environment. Nowadays, almost all businesses including small to big organizations need the data and insight from it. While an organization is looking for its potential customers and their preference, big data plays a significant role. Therefore, the companies have been using big data to make data-driven strategies that help them to compete with the competitors. This paper discussed the case studies on China Eastern Airlines (CEA) used the Oracle big data that helped them to know their services, know the relationship of passengers and aircraft members, and even know when to replace the parts of the aircraft. Besides, the paper explained how we can use big data for production, predictive maintenance, and prevent fraud and compliances. The paper summarized that big data plays a significant role for almost all the industries, but for the airlines, the production and financial sector has their crucial roles. 


Cardenas, A. A., Manadhata, P. K., & Rajan, S. P. (2013). Big data analytics for security. IEEE Security & Privacy, 11(6), 74-76.

Choi, T. M. & Lambert, J. H. (2017). Advances in risk analysis with big data. Risk Analysis, 37 (8), pp. 1435-1442.

China Eastern Airlines (2022, May). Introducing CEA

Daily, J., Peterson, J. (2017). Predictive Maintenance: How Big Data Analysis Can Improve Maintenance. In: Richter, K., Walther, J. (eds) Supply Chain Integration Challenges in Commercial Aerospace. Springer, Cham

Fang, B., & Zhang, P. (2016). Big data in finance. In Big data concepts, theories, and applications (pp. 391-412). Springer, Cham.

Labrinidis, A., & Jagadish, H. V. (2012). Challenges and opportunities with big data. Proceedings of the VLDB Endowment, 5(12), 2032-2033.

Manyika, J., Chui, M., Brown, B., Bughin, J., Dobbs, R., Roxburgh, C., & Byers, A. H. (2016). Big data: The next frontier for innovation, competition, and productivity. McKinsey & Company

Oracle. (2021, June). Data Management, defined

Oracle (2022, May). What is Big Data?

Oracle (2022, May). China Eastern Airlines adopts Oracle Big Data to enhance flight safety




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