Time Series Data Mining: A Case Study With Big Data Analytics Approach

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....

Parallel Time Series Modeling - A Case Study of In-Database Big Data Analytics

MADlib is an open-source library for scalable in-database analytics. In this paper, we present our parallel design of time series analysis and implementation of ARIMA modeling in MADlib’s framework. The algorithms for fitting time series models are intrinsically sequential since any calculation for a specific time t depends on the result from the previous time step t − 1. Our solution paralleli...

A Survey on Big Data Analytics in Data Mining

Querying of Time Series for Big Data Analytics

Time series data emerge naturally in many fields of applied sciences and engineering including but not limited to statistics, signal processing, mathematical finance, weather and power consumption forecasting. Although time series data have been well studied in the past, they still present a challenge to the scientific community. Advanced operations such as classification, segmentation, predict...

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 ...