核心概念
The author explores the challenges and solutions in architecting data-intensive applications, emphasizing the importance of data quality for effective decision-making and operational processes.
摘要
The content delves into the significance of data architecture in managing and utilizing data efficiently. It discusses various architectures like Lambda and Kappa, highlighting the importance of data quality dimensions such as accuracy, completeness, consistency, timeliness, validity, and uniqueness. The thesis aims to enhance the quality of data-intensive applications through Model Driven Engineering techniques.
統計資料
Google generates around 2.5 million Terabytes per day.
IDC expects data to reach 175 zettabytes by 2025.
Approximately 200 million emails are sent every minute.
300000 tweets are posted every minute.
100 hours of YouTube videos are uploaded every minute.
引述
"The accuracy and reliability of insights derived from data are directly linked to its quality." - Author
"Maintaining high-quality data is crucial for making informed decisions based on reliable insights." - Author