Contemporary datacenters house tens of thousands of servers. The servers are closely monitored for operating conditions and utilizations by collecting their performance data (e.g., CPU utilization). In this paper, we show that existing database and file-system solutions are not suitable for warehousing performance data collected from a large number of servers because of the scale and the comple...

Data warehousing systems populating processes are responsible for loading their data repositories – the data warehouses – with information they extract from operational sources. The tasks that integrate these processes are the most complex ones that we can find in a data warehousing system. For a flawless implementation, modelling these processes previously is important so that a correct set of...

This paper presents an insight into the emerging concept of Master Data Management (MDM) and highlights issues that both academics and business managers should consider to better understand the meaning of this ‘hot topic’. This critical reflection paper is forward looking and attempts to make sense of the MDM concept and highlight the issues associated with implementation. We argue that both th...

This paper provides an overview of Data warehousing, Data Mining, OLAP, OLTP technologies, exploring the features, new applications and the architecture of Data Warehousing and data mining. The data warehouse supports on-line analytical processing (OLAP), the functional and performance requirements of which are quite different from those of the online transaction processing (OLTP) applications ...

Contemporary datacenters house tens of thousands of servers. The servers are closely monitored for operating conditions and utilizations by collecting their performance data (e.g., CPU utilization). In this paper, we show that existing database and file-system solutions are not suitable for warehousing performance data collected from a large number of servers because of the scale and the comple...

Enterprises have gathered operational business information frommultiple structured data sources and stored it in a central repository, called data warehousing, for decision support functionalities and data analysis. The enterprises are now realizing to integrate their entire information sources, including "unstructured" contents, for deeper and richer information analysis. Several applications,...

With the rise of the Internet and the development of various electronic information resources, mining useful information from large databases has become one of the most important issues in information research for users. Data warehousing plays the key role in providing data for data mining tools to explore knowledge. However, there are still many problems that cause users to spend extra time to...

Defining data warehouse requirements is widely recognized as one of the most important steps in the larger data warehouse system development process. This paper examines the potential risks and pitfalls within the data warehouse requirement collection and definition process. A real scenario of a large-scale data warehouse implementation is given, and details of this project, which ultimately fa...