The variety of data is one of the most challenging issues for the research and practice in
data management systems. The data are naturally organized in different formats and …

Big Data Systems (BDSs) are an emerging class of scalable software technologies whereby
massive amounts of heterogeneous data are gathered from multiple sources, managed …

This paper argues that the data warehouse architecture as we know it today will wither in the
coming years and be replaced by a new architectural pattern, the Lakehouse, which will (i) …

As a concept and disciplinary practice, resilience analysis has evolved rapidly within the
twenty-first century. This is driven in large part by the growing complexity in everyday …

Data is at the center of many challenges in system design today. Difficult issues need to be
figured out, such as scalability, consistency, reliability, efficiency, and maintainability. In …

The first edition of this book appeared in 1991 when the technology was new and there were
not too many products. In the Preface to the first edition, we had quoted Michael Stonebraker …

Since the late 1970s, relational database technology has been adopted by most
organizations to store their essential data. However, nowadays, the needs of these …

Big Data is used in decision making process to gain useful insights hidden in the data for
business and engineering. At the same time it presents challenges in processing, cloud …

In many organizations, it is often challenging for users to find relevant data for specific tasks,
since the data is usually scattered across the enterprise and often inconsistent. In fact, data …

Modern applications often need to manage and analyze widely diverse datasets that span
multiple data models [1],[2],[3],[4],[5]. Warehousing the data through Extract-Transform-Load …