data miningData warehouses have been developed to answer the increasing demands of quality information required by the top managers and economic analysts of organizations. Their importance in now a day business area is unanimous recognized, being the foundation for developing business intelligence systems...
A data warehouse system can take meaningless data and, using intense analytical processing, offer insight into changing market conditions before they occur. The capability to optimize customer interactions and supply chain operations is becoming a source of great competitive advantage. This Hon Guide ...
Example: A healthcare provider seeking to reduce readmission rates needs to be able to measure this headline rate, as well as quantify the actions taken that impact readmission and capture quantitative patient experience data for text mining. In this way, the organization can identify trends, optim...
Data at the physical network layer, including physical entity data, space data, resource data, protocols, interfaces, routes, signaling, processes, performance, alarms, logs, and status, is collected and stored to the data warehouse in real time or non-real time. The data is th...
The real challenge to enterprises in deep- level transformation is digitalizing the physical world. • Challenge 2: Quickly Acquiring Talent for Digitalization During Rapid Technological Innovation Digital transformation requires a wide range of new technologies, such as cloud, b...
A small data warehouse was designed for use by undergraduate students in a data-mining course. Our design included the selection of appropriate hardware, software, and real world data plus the building of the interface between the warehouse and the software used for mining its contents. Guides we...
In the future, such a data center can be built in just a few months, meeting the requirements for rapid service rollout. As big data, AI, neural networks, and other technologies gain traction, digital infrastructure O&M will become intelligent and automated. With massive amounts of data and...
In our previous work, we have analyzed the shortcomings of existing business intelligence (BI) theory and its actionable capability. One of the works we have presented is the ontology-based integration of business, data warehousing and data mining. This
Regardless of whether you have acknowledged it, your business already has a culture of decision-making. That culture might not be geared toward a data-driven approach. All too many companies subscribe to the “HIPPO” (highest-paid person in the office) method of decision-making, whereby the ...
Under a Creative Commons license Open accessAbstract Over the last decade, collecting massive volumes of data has been made all the more accessible, pushing the building sector to embrace data mining as a powerful tool for harvesting the potential of big data analytics. However repetitive challenges...