The Challenges, Strategies, and Roles of Database Technology in the

Big Data Era: A Case Study of the Push System in E-Commerce

Haoming Zhang

Physics Department, Capital Normal University, Beijing, China

Keywords: Live E-Commerce, Big Data, Database, Strategies.

Abstract: In the era of big data, live e-commerce has seen explosive growth, putting pressure on instant and tailored

advertising. This research aims to refine ad systems, focusing on delivering ads promptly and accurately to

improve user experience and increase platform revenue. The study uncovers that processing extensive data

can hinder the speed of ad delivery, which can negatively impact user satisfaction and, consequently, sales.

To address this, e-commerce platforms are in need of more accurate recommendation systems to facilitate

personalized ads, which depend on a thorough analysis of consumer behavior. There exists a challenge where

existing algorithms may not fully comprehend or anticipate user needs, leading to a misalignment between

the ads served and the actual interests of users. In the context of increasingly stringent data protection laws,

it is imperative for ad systems to manage user data with greater care and legality, thereby ensuring compliance

with regulations and safeguarding user privacy.

1 INTRODUCTION

Big data is widespread today. Live e-commerce

boosts consumer spending. It personalizes shopping.

Live e-commerce enhances the buying experience. It

makes purchases engaging. It makes purchases

immediate. Yet, as the user base and product

assortment expand, the advertising mechanisms of

these platforms are under pressure to maintain

responsiveness and enhance the precision of their

recommendations. By establishing a database

security guarantee system and optimising the method

of user access to the database, the real-time and

accuracy of advertisement push can be effectively

improved, and the effect of personalised

recommendation can be enhanced(Feng, Yang, Li,

Y, 2021).

These optimisation measures include the use of

technical means, management mechanisms, and audit

trails to ensure security and compliance with data

collection and processing.Feng Wenlu et al. discussed

how traditional media can be transformed through the

live e-commerce mode, and proposed the driving

forces for the development of media live e-

commerce, including the accelerated layout of

https://orcid.org0009-0001-9991-1220

Internet platforms, the shift in user demand under the

digital survival mode, the promotion of relevant

regulations, and the in-depth integration of

media.These factors have pushed the growth of the

live e-commerce industry, creating new platforms and

user bases for ad push(Feng, Yang, and Li,

2021).Feng Qinqun proposed that in the context of

big data, a database security protection system should

be established to improve the external environment of

the database system, apply technical means,

implement the management mechanism, strengthen

the audit trail and comprehensively back up the data.

This is a meaningful way for live e-commerce

platforms to ensure data security and user privacy

protection when dealing with massive amounts of

user data(Feng,2013).Tang Tao proposes a method of

optimising the user access database of the live e-

commerce platform based on big data, screening the

goods frame number images corresponding to the

time of the live video through the link of the

recommended goods on the user access to the live

video, extracting the content features in the enhanced

image of the goods frame number, comparing and

screening the various content features corresponding

to the needs of the user access to the goods, and

arranging them in sequence. This method helps

Zhang, H.

The Challenges, Strategies, and Roles of Database Technology in the Big Data Era: A Case Study of the Push System in E-Commerce.

DOI: 10.5220/0012918100004508

Paper published under CC license (CC BY-NC-ND 4.0)

In Proceedings of the 1st International Conference on Engineering Management, Information Technology and Intelligence (EMITI 2024), pages 183-187

ISBN: 978-989-758-713-9

183

improve the ad push effect of the live e-commerce

platform, and enhances the user experience and

conversion rate by optimising how users access the

database(Tang, 2020).

In addition, database technology is improving

data processing capabilities through distributed

processing and real-time analysis in the live e-

commerce industry to meet the challenges of massive

user interactions and product data. However, how to

achieve in-depth access to data while protecting user

privacy and improving the accuracy and real-time

performance of personalised recommendations

remain major problems for researchers. Live e-

commerce platforms need to optimise their database

systems to support more efficient ad push and user

behaviour analysis while observing data security (He,

2024).

Against this background, this study proposes an

optimisation strategy for personalised ad push on live

e-commerce platforms based on existing theories and

patents. Adopting the literature review method, this

study thoroughly analyses the optimisation strategy

of personalised ad push system for live e-commerce

platforms. It explores the key role of database

technology in processing massive user data,

improving the effect of ad push, and protecting data

security. This paper not only aims to improve the real-

time and accuracy of ad push, but also devotes itself

to achieving more accurate personalised

recommendation by deeply accessing user data under

the premise of complying with data security

regulations. The meaning of this study is that it can

not only provide theoretical support for the ad

revenue of live e-commerce platforms but also

discuss how to provide a more personalised and high-

quality user experience under the premise of

protecting user privacy, with the development of the

live e-commerce industry(He, 2024).

2 THE ROLE OF DATABASES IN

AD PUSH

2.1 Database Principles

A database is a computer software system that

organises, stores, manages and retrieves massive data.

It is not only a simple data storage warehouse, but a

complex system that ensures data integrity, security

and efficient access. Live online shopping relies on

databases. Databases store customer profiles, product

catalogs, and transaction histories. They keep the

platform running well and help user interactions.

Databases solve data management challenges

before computers, filing cabinets and card indexes

stored and retrieved information. These methods

became inefficient with more data.

Databases use data models and database

management systems (DBMS). Data models show

data structure and connections with tables. DBMS has

tools for creating, querying, changing, and deleting

data. It also protects data, ensures security, manages

access, and helps recover data. In live e-commerce,

databases process consumer behavior data quickly.

This helps make personalized recommendations and

place ads strategically.

2.2 The Role of Databases in Ad Push

Database technology is very important in live online

shopping. Tang Tao says using databases can

improve how users interact with products in live

streams. This makes ads more personalized and

enjoyable. It does this by looking closely at product

images and studying how users interact with items.

Feng Qinqun says protecting databases is crucial.

This means improving the database environment,

using advanced strategies, managing it well, tracking

activity, and backing up data. These steps help keep

databases secure, stop unauthorized access, and keep

data reliable and accessible(Feng, 2013).

At first, in live online commerce, databases store

basic data like customer messages, product info, and

sales records. They help manage user accounts,

handle orders, and offer searches. As live e-

commerce grows, databases now work closely with

key parts of the business, like live shows, user chats,

and product suggestions.For example, by analyzing

user interaction data during live broadcasts in real

time, the database can support a personalized

recommendation system that pushes users with

products they may be interested in. By analyzing

users' browsing, purchasing and interaction data, a

detailed user profile is constructed for personalized

recommendation. Intelligent product

recommendations are implemented using user

profiles and behavioral data to improve user

satisfaction and conversion rates. Optimize

advertisement placement strategy and improve

advertisement effect by analyzing user data in real

time. Supported the rapid processing of online

transactions, including order creation, payment

processing, and logistics tracking. Provide data

support for platform operations and help merchants

and platforms make smarter business decisions.

According to Min Li, database advertising design

plays a role in storing and analyzing the design

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elements of advertising language to help build an

effective advertising communication strategy. The

database can store information such as the title,

content, and promissory nature of advertisements,

and by analyzing this information, it can help

advertisers understand which advertising languages

are more likely to stimulate consumers' desire to buy,

thus realizing the effective push of advertisements(Li,

2021).

Huang Rui says databases collect data on what

users do online, like clicking, browsing, and

interacting. This data helps analyze users' habits and

likes. Marketers use these analyses to find and group

their target audiences. They make ads that fit these

groups' needs, making the ads more appealing and

effective(Huang, 2023.

Live streaming commerce platforms use big data

to understand their users better. They want to target

ads more accurately. Tang Tao says by looking at

how users watch live streams, ads can be made more

relevant. This means finding what products users like

and matching ads to those preferences. Tengfei Gao

and others say databases are key for personalizing ads.

They keep track of users' past actions, like ads they

clicked and things they bought. By studying this data,

ad platforms learn users' likes and guess what they

might want in the future. This leads to personalized

and effective ad suggestions(Gao,and Qu 2023).

3 DATABASE OPTIMIZATION

TECHNIQUES

3.1 Technology Examples

In live e-commerce, better database technology helps

make user experience better and ad delivery more

efficient. Feng Qinqun's research shows that making

good indexes, like B-trees, hash tables, or full-text

indexes, can greatly speed up how fast data is found.

This is very important when there's lots of data to

handle(Feng, 2013).In addition, Yuan Yuan He in his

essay emphasized the importance of query

optimization, which can reduce unnecessary data

accesses and computations by analyzing and

rewriting SQL queries, thus improving the efficiency

of database operations(He, 2024).

In live e-commerce, the application of database

optimization techniques is not limited to improving

query speed and optimizing query statements. Ying

Wu discusses the application of real-time data

analytics in live e-commerce in her research. With

ClickHouse database (which provides high-

performance data analytics and supports fast querying

and processing of hundreds of millions of data)

processing user interaction data, such as likes,

comments, and shares, in real time, the database is

able to quickly update the user profiles and achieve

more accurate ad targeting. At the same time, Yao Ge

mentioned in his article that for frequently accessed

advertising content, the use of caching technology

can reduce the reading pressure on the database and

improve the system's response speed, which is

especially important for the fast-changing advertising

content on live e-commerce platforms (Wu, 2024;

Yao, et al., 2023).

3.2 Optimization Recommendations

In the future development of live e-commerce ad

push, advances in database technology will be key.

First, to meet the challenge of data privacy protection,

databases should adopt more stringent security

measures and privacy-preserving algorithms, such as

differential privacy and homomorphic encryption, to

ensure the security of user data during analysis and

use. Ad content personalization and compliance need

databases to quickly update and adjust ad strategies.

They must follow different region and platform rules.

This might mean creating better algorithms to find

and block non-compliant ads. Databases must also

adapt quickly to changing rules, data structure, and

search criteria.

Handling data from many platforms requires

databases good at combining different data sets.

Solutions might include making a standard data

model. They might also involve systems for regular

data sync and sharing across platforms. This ensures

a consistent ad experience for users on any platform.

It also means databases need strong data transfer and

change tools, moving data smoothly between systems

and platforms.

Using cloud-native databases and microservices

can improve live e-commerce data management. It

makes the ad system handle more traffic, reducing

costs. Smart database tools, like auto index tuning and

query analysis, improve ad delivery's effectiveness

and accuracy.

For this progress, industry cooperation and setting

common standards are key.Providers of database

solutions, online marketplaces, and regulatory bodies

must collaborate to formulate consistent data

protocols and interoperability guidelines. This

facilitates the seamless exchange and consolidation of

data across various platforms.Through these practical

measures, live e-commerce ad push systems will be

able to better serve users while protecting user

The Challenges, Strategies, and Roles of Database Technology in the Big Data Era: A Case Study of the Push System in E-Commerce

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privacy and improving ad compliance and

effectiveness.

4 CONCLUSIONS

The research in this paper focuses on the optimization

strategy of personalized ad push system for live e-

commerce platform. The research adopts the method

of literature review, by analyzing the existing theories

and patents, and combining with several papers in

related fields, it discusses the challenges faced by live

e-commerce in the context of big data, and how to

improve the real-time, accuracy and user experience

of ad push through the application and optimization

of database technology.

It was found that the ad push system of live e-

commerce platforms faces problems with insufficient

real-time performance and poor recommendation

accuracy when dealing with massive user data. To

solve these problems, the study proposes a series of

optimization strategies. First, a database security

guarantee system is established by improving the

external environment of the database system,

applying technical means, implementing

management mechanisms, strengthening audit trails

and comprehensively backing up data to ensure data

security and user privacy protection. Second, an

optimization method of user access database for live

e-commerce platform based on big data is proposed

to improve the personalization level and user

experience of ad push by screening and extracting the

content features in the images of product frames and

users' behavioral data when they access the

products.Moreover, the research underscores the

pivotal role that database technology plays in the live

e-commerce sector, which encompasses not only the

preservation and handling of fundamental data like

customer details, merchandise descriptions, and sales

histories, but also the facilitation of tailored

recommendation algorithms and the enhancement of

advertising delivery strategies.

Looking ahead, live commerce platforms are

expected to refine their database infrastructure to

enhance ad delivery efficiency and consumer

behavior analysis while adhering to stringent data

protection guidelines. This will involve implementing

more robust security protocols and privacy-

preserving data processing techniques, creating smart

algorithms that can identify and filter out

inappropriate ad content automatically, and setting up

systems that facilitate the synchronization and

exchange of data across different platforms.

Concurrently, embracing cloud-based databases and

microservices design will offer greater adaptability

and scalability in data management for live commerce.

As technology continues to evolve, this research is

poised to offer innovative approaches and strategies

for personalized ad targeting, contributing to the

sustainable growth of the live e-commerce sector.

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