In the past 30 years, companies have invested significant funds and manpower in the construction of information systems. The characteristic of information system construction is to be project-oriented with a focus on business, automating and streamlining manual processes through computer technology. These information systems often consist of application programs and their corresponding database systems, which are not interconnected, leading to the formation of isolated data islands within each enterprise. Today’s enterprises are facing fierce homogenized competition and are embracing digital transformation as a strategic initiative, aiming to empower their businesses through data, generate new value, improve user experience, and enhance customer retention, among other objectives. Data allows businesses to gain insights into sales, marketing, channels, operations, and production reality. It also provides valuable input for data scientists, machine learning, and artificial intelligence, enabling the creation of greater value for enterprises.

However, the issue of data isolation is becoming a major obstacle to the digital transformation of these enterprises. For example, an airline company may have more than 80 systems related to passengers. Customer information is scattered across disconnected business systems, making it impossible to obtain a complete profile, travel details, or interaction history of a customer, regardless of the channel. This leads to the inability to provide the best customer service experience or achieve precise targeting and other business scenarios, directly affecting customer retention and sales growth.

In addition, enterprises are increasingly demanding more data, and traditional data delivery has become a major bottleneck for most enterprises in terms of data monetization. Coupled with the increasingly complex on-premises and cloud environments, effective, fast, efficient, and real-time data capabilities will be one of the most critical factors for competitiveness in enterprises today.

In this technical whitepaper, we will provide a detailed explanation of how Tapdata addresses the challenges mentioned above. We will delve into the Tapdata solution and compare it with traditional big data solutions, highlighting its differences, advantages, working principles, technical architecture, and key capabilities. Additionally, we will present the main business scenarios and product strengths of Tapdata. Finally, this whitepaper includes performance parameters and deployment architecture of Tapdata as a reference.