1. Introduction

In the era of information digitization, big data has gained the attention of the whole society and rapid development in the past few years, and the shadow of big data applications can be seen in almost every industry. The application scope of big data is becoming more and more extensive, and the application of the industry is also more and more, we can see almost every day - some novel applications of big data, and the value of big data has also been reflected in all aspects. Big data currently has more application areas mainly in the Internet, finance, health care, education, government, and other industries, the application of the environment is not the same. As a representative of the e-commerce industry, Taobao, big data is an indispensable way to revolutionize the reform, but also the core of competitiveness. And Taobao's database is derived from the Alibaba database.

This study on Taobao and the Alibaba database reveals key insights for both scholars and business professionals. Academically, the interplay between Taobao and Alibaba's database can guide future research on big data's role in e-commerce transformation. For businesses, the study showcases the transformative power of a well-structured database, emphasizing its value in personalizing customer experiences, predicting market trends, and strengthening supplier ties. The findings hint at the urgency for businesses to prioritize data analytics, suggesting that those lagging in this arena might face competitive setbacks.

2. The Importance of Big Data in Business Transformation

Characterized by its volume, velocity, variety, veracity, and value, big data provides businesses with powerful tools to gain actionable insights. During business transformation, big data can facilitate the following:

First, accurate strategy: By analyzing huge data sets, companies can predict market dynamics and develop strategies with a higher probability of success.

Second, Customer-centric development: Data analysis first defines the target group of the product and then analyzes the behavior of the consumer through big data to accurately analyze the user's preferences, purchasing power, and purchasing habits, so as to be able to provide tailor-made products that make the consumer have a tendency to buy.

Third, streamlining operations: By analyzing huge data sets, companies can predict market dynamics and develop strategies with a higher probability of success.

Forth, simplify the operation mode: through the information intelligence tool to collect information for modeling and mining, so as to carry out specific detailed classification and analysis of the user, this operation needs to have huge user information as the basis, and Alibaba's WeChat, the Internet software platform can help Alibaba database to collect a huge amount of information about the user. This explains the resource allocation, supply chain optimization, and overall operational efficiency of a large database.

3. The Power Duo: Taobao and Alibaba

Taobao, one of the world's leading e-commerce platforms, provides a perfect example of how companies can utilize big data for transformation. Underpinning Taobao's success is the massive Alibaba database. The database is a huge repository of information, the lifeblood of Taobao, one of the world's most important e-commerce platforms, and the nerve center of Taobao's operations, which is involved in guiding everything from product recommendations to final after-sales services. They are under the unified price company, which also brings Taobao many benefits:

First, large-scale personalization: based on Taobao's original huge user base, and then through continuous analysis of the user's online footprint, Taobao improved its recommendation engine, promoted products that meet personal preferences, in order to get more users to come, and then to Alibaba's database to get more users to analyze the data, so a virtuous cycle, making Taobao and Alibaba database bigger and better [1].

Second, market forecasting: past transaction data and user information collected from Internet tools such as WeChat can better help Taobao predict future market trends and provide guidance for inventory and marketing decisions [2].

Third, enhanced Supplier Visualization: Big data allows for increased insight into product performance, which enables Taobao to provide actionable feedback to many suppliers, which allows suppliers to make more improvements, thus facilitating the relationship between users and suppliers, and increasing sticky users to Taobao while allowing suppliers to gain more trust, thus creating a collaborative development environment [3]. The literature is analyzed and validated.

4. Literature Analysis and Validation

The importance of big data in business transformation becomes clear through several literature reviews. For example, Manyika emphasizes the importance of big data analytics as a key foundation for businesses to compete, supporting a new wave of productivity growth, innovation, and consumer surplus; for example, retailers leveraging big data can increase their operating margins by more than 60% [4].

Similarly, in Mehul Rajput's article, it is suggested that big data can be of great help in developing practices, strategies, and procedures as consumers change their preferences and spending power at any time as the wider economy varies, which also allows big data to change the prices and types of products they are pushing by receiving timely and up-to-date data from consumers [5]. Yicai emphasizes the reintegration and distribution of customer resources by big data behind Taobao, because people in different regions have different consumption levels and different consumption habits. For example, consumers in coastal cities are less likely to buy seafood than those in inland cities, and the consumption habits of urban and rural residents are different, with urban residents spending more on food, housing, clothing, education, culture, and entertainment than rural residents [6].

In "How to Personalize the Customer Experience with the Help of Big Data", the personalization strategy brought by big data is highlighted, for example, the article says that 77% of people use Google search before purchasing goods, while 84.3% of people use Google search before purchasing goods, and 84.3% of people use Google search before purchasing goods. For example, the article states that 77% of people will use Google search before making a purchase, while 84.3% will check out commercial websites [1]. Furthermore, in a white box article on data, the role of data in market forecasting is revealed [2].

5. Suggestions

Given the transformative role of big data, as emphasized by the synergy between the Taobao and Alibaba databases, it is important for policymakers in both the public and private sectors to be informed and proactive. Based on the observations of this study, the following policy recommendations are made for the sustainable and ethical use of big data analytics in business transformation:

5.1. Create education and training

The government should collaborate more with academic institutions, research institutes, and businesses to design and push through curricula focused on big data analytics, AI, especially by including this curriculum in high schools and universities, and create as many events, competitions, and contests as possible in the context of big data and AI. The benefit is that by cultivating this talent nationwide, more of it can be harvested and companies can realize the benefits of big data.

5.2. Infrastructure level

Encourage private companies to invest and build data centers and cloud computer centers, and support the creation of a national database center through which companies of all sizes can trade or access data exchanges, thus enhancing datamining and democratizing access to data.

5.3. Regulatory authorities

Establish a data security department to protect the privacy and security of users, as well as to combat the illegal trade of user data by companies that could jeopardize the national level. Consumer rights associations can be set up to act as a bridge between users and civil society, and companies to promote cooperation between them, so that users can proactively improve their data and companies can avoid violating their privacy [7].

5.4. Cross-sectoral cooperation

Support the exchange of data across industries on the platform to make people's lives easier and faster, and ensure data security and privacy through data security departments.

5.5. Increase investment and innovation

Encourage and support companies to set up competitions with prizes to stimulate competition among university and college students to acquire developmental talent. And the state should enact incentives to encourage companies to innovate.

5.6. Setting Harmonization and Quality Standards

Advocate for standardized protocols in data collection, storage and analysis to ensure the consistency and reliability of the insights derived. Establish certification bodies to audit and verify the quality of companies' big data processes. Consumer rights compel companies to provide consumers with clear insights about how their data is being used. Promote the development of tools that enable consumers to control the data they share with businesses.

5.7. Environmental Factors

Given the energy consumption of massive data centers, develop guidelines to promote green and sustainable practices for big data infrastructure. Provide tax incentives to companies that implement energy efficiency measures in their data operations. In short, the case of the Taobao and Alibaba databases illustrates that big data is not just a tool, but a key force driving the transformation of modern businesses. However, in order to realize its full potential and ensure responsible use, well-crafted policies are essential. By following these recommendations, policymakers can ensure that businesses maximize the benefits of big data while safeguarding consumer interests and ethical considerations [8-10].

6. Conclusion

It is evident from the extensive literature that big data is a valuable asset in the contemporary business environment. The symbiotic relationship between Taobao and Alibaba databases exemplifies how companies can thrive in today's digital deluge and utilize data not only as information but as a catalyst for overall transformation. It's not just about processing massive amounts of information; it's about turning that information into actionable insights that drive business growth. While this paper provides valuable insights into the transformative role of big data in business transformation, particularly in the context of the Taobao and Alibaba databases, it has some limitations.

This paper focuses mainly on the Taobao and Alibaba databases, which, although characterized, are mostly attributed to the Alibaba database and Taobao itself, which are two powerhouses as one of the largest databases known to exist within China and one of the best e-commerce companies known to exist within China and indeed within the world. Therefore, this does not cover the full impact of the database on different industries and regions. Limitations of the methodology used to analyze the database: most of the content of this paper is a reference to the research obtained from other texts, I just add to the icing on the cake, plus some of my own thinking, but not entirely dependent on their own data analysis and research results. Because the study requires a lot of specialized knowledge and data support, and it has to face many complex technical issues and challenges. Determination of future research directions. Future research should be based on a selection of reference companies, rather than the top companies such as Taobao and Alibaba data, so that more general insights can be obtained. The algorithms of Big Data can be analyzed through the study of a database to obtain the shortcomings and strengths of the database.