Big data analytics associated with database searching, mining, and analysis can be seen as an innovative IT capability that can improve firm performance. Even though some leading companies are actively adopting big data analytics to strengthen market competition and to open up new business opportunities, many firms are still in the early stage of the adoption curve due to lack of understanding ...

Nowadays, companies rely more than ever on stored data to support decision making. However, outdated data may result in wrong decisions and economic losses. Thus, measuring data currency is extremely important. Existing metrics for currency either assume that their input parameters are given, or estimate them statistically, which may not always be possible in applications and especially in the ...

Enterprises have a large amount of data available, represented in different formats normally accessible for different specialists through different tools. Integrating existing data, also those from more informal sources, can have great business value when used together as discussed for instance in connection to big data. On the other hand, the level of integration and exploitation will depend b...

Many data analytics classes utilize canned data, already cleansed, and with simplified scenarios for students to perform analysis. To better train students to tackle real-world analytics problems, using big data from a real company builds on prior research on the effectiveness of experiential learning. In this study, we introduced experiential learning into a data analytics class by working on ...

The performance of classification models extremely relies on the quality of training data. However, label imperfection is an inherent fault of training data, which is impossible manually handled in big data environment. Various methods have been proposed to remove label noises in order to improve classification quality, with the side effect of cutting down data bulk. In this paper, we propose a...

The paper examines the opportunities in and possibilities arising from Big Data in retailing, particularly along five major data dimensions data pertaining to customers, products, time, (geo-spatial) location and channel. Much of the increase in data quality and application possibilities comes from a mix of new data sources, a smart application of statistical tools and domain knowledge combined...