Uncertainty and grey data analytics

A Framework for Uncertainty-Aware Visual Analytics in Big Data

Visual analytics has become an important tool for gaining insight on big data. Numerous statistical tools have been integrated with visualization to help analysts understand big data better and faster. However, data is inherently uncertain, due to sampling error, noise, latency, approximate measurement or unreliable sources. It is very important and vital to quantify and visualize uncertainties...

Uncertainty-aware Visual Analytics for Spatio-temporal Data Exploration

A Fuzzy TOPSIS Approach for Big Data Analytics Platform Selection

Big data sizes are constantly increasing. Big data analytics is where advanced analytic techniques are applied on big data sets. Analytics based on large data samples reveals and leverages business change. The popularity of big data analytics platforms, which are often available as open-source, has not remained unnoticed by big companies. Google uses MapReduce for PageRank and inverted indexes....

Application of Big Data Analytics in Power Distribution Network

Smart grid enhances optimization in generation, distribution and consumption of the electricity by integrating information and communication technologies into the grid. Today, utilities are moving towards smart grid applications, most common one being deployment of smart meters in advanced metering infrastructure, and the first technical challenge they face is the huge volume of data generated ...

Data Science and Analytics

Thanks to advancement of sensing, computation and communication technologies, data are generated and collected at unprecedented scale and speed. Virtually every aspect of many businesses is now open to data collection; operations, manufacturing, supply chain management, customer behavior, marketing, workflow procedures and so on. This broad availability of data has led to increasing interest in...