Big Data - Analytics Engine for Digital Transformation: Where is IS?
2015
- 860Usage
Metric Options: CountsSelecting the 1-year or 3-year option will change the metrics count to percentiles, illustrating how an article or review compares to other articles or reviews within the selected time period in the same journal. Selecting the 1-year option compares the metrics against other articles/reviews that were also published in the same calendar year. Selecting the 3-year option compares the metrics against other articles/reviews that were also published in the same calendar year plus the two years prior.
Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Metrics Details
- Usage860
- Abstract Views520
- Downloads340
Artifact Description
It is estimated that 90% of today’s existing data in the world has been created in the last two years (IBM 2015). Four Zettabytes (4 trillion GB) of data are created every year. Data come from sensors, scientific instruments, medical devices, smart phones; digital media including text, video, audio, email, blogs, postings, twitter feeds, click streams, financial and other transactions. The big promise here is that together with traditional data sources, big data offers unprecedented opportunities to study the “pulse of humanity” at granularity levels that were never available before. For the last few years, government agencies, businesses, consultants, scientists and academics from various disciplines have been challenged with the very complex issues of how to harness big data, how to analyze big data an what to do with big data. How to capitalize on the promise of big data? The IS discipline has been challenged as well. Understanding data processing, storage, integration are integral to our field. Transforming data to information to knowledge is the essence of what we do. Supporting decision making with information and analytics has been part of our teaching and research arsenal since the concept of Decision Support Systems was introduced in the 70’s.
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