Big data preprocessing: methods and prospects

Abstract

The massive growth in the scale of data has been observed in recent years being a key factor of the Big Data scenario. Big Data can be defined as high volume, velocity and variety of data that require a new high-performance processing. Addressing big data is a challenging and time-demanding task that requires a large computational infrastructure to ensure successful data processing and analysis.

Data pre-processing: a case study in predicting student’s retention in MOOC

“…Attribute selection process select only relevant attributes for the study such as excluding all other video event (video speed, video new speed, video current time and video old time) which is not the focus of this study. The process is important for e-learning including MOOC, which has many attributes comprised in a file [12]. This process makes the later work easier with less memory consumption and researcher can focus more on objective of the task.…”

“…In [7,12] explain that open issue. Moreover, for eexpert who ask the question to avoid any lose context meaning [8].…”

“…There are various techniques for normalization like binarizer, normalizer and standardscaler [12]. For e-learning variables, common technique like min-max can be used [9].…”

Key Problems of Data Management in Data Center in Big Data Context

“…Data preprocessing [8] usually includes removing noise data, reducing redundant data, and cleaning the dirty data. Data preprocessing can ensure the quality and reliability of the following data integration stages.…”

Data mining technology based on rough set and genetic algorithm under large data environment

“…Data analysis is the foundation of scientific research, many scientific research is based on data collection and analysis in the current business activities [1][2][3]. The data analysis is always and some special groups of people high IQ behavior, because not every ordinary person can predict future trends or make the right decisions from past sales, but as a business or industry continues to accumulate business data, especially due to the popularity of the database, To manually sort out and understand such a large data source has been the existence of efficiency, accuracy and other issues.…”