This study presents the challenges faced and the solutions adopted while evolving the web-based graphical user interface (GUI) of a tabular data preparation tool from in-memory fitting to Big Data sets. Traditional standalone processing and rendering solutions are no longer usable in a Big Data context.
Tag: Big data
Today׳s supply chain professionals are inundated with data, motivating new ways of thinking about how data are produced, organized, and analyzed. This has provided an impetus for organizations to adopt and perfect data analytic functions (e.g. data science, predictive analytics, and big data) in order to enhance supply chain processes and, ultimately, performance.
Open Data (OD) is one of the most discussed issue of Big Data which raised the joint interest of public institutions, citizens and private companies since 2009. However, the massive amount of freely available data has not yet brought the expected effects: as of today, there is no application that has fully exploited the potential provided by large and distributed information sources in a non-trivial way, nor any service has substantially changed for the better the lives of people.
Cloud computing is a powerful technology to perform massive-scale and complex computing. It eliminates the need to maintain expensive computing hardware, dedicated space, and software. Massive growth in the scale of data or big data generated through cloud computing has been observed. Addressing big data is a challenging and time-demanding task that requires a large computational infrastructure to ensure successful data processing and analysis.
This paper is about the conceptual development of the Big Data Quality Framework for Malaysia’s Public Sector Open Data Initiative (My-PSODI). At the moment, there is a lack of Big Data Quality Framework in existence particularly that is focusing on the specific context and needs of Malaysia’s Public Sector Open Data initiative.
