Data Science for Business: What You Need to Know about Data Mining and Data-Analytic Thinking
Impact in
Classified as
- Authors
- Foster ProvostTom Fawcett
In The Last Decade
doi.org/w73471307 →Countries where authors are citing Data Science for Business: What You Need to Know about Data Mining and Data-Analytic Thinking
This map shows the geographic impact of Data Science for Business: What You Need to Know about Data Mining and Data-Analytic Thinking. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Data Science for Business: What You Need to Know about Data Mining and Data-Analytic Thinking with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Data Science for Business: What You Need to Know about Data Mining and Data-Analytic Thinking more than expected).
Fields of papers citing Data Science for Business: What You Need to Know about Data Mining and Data-Analytic Thinking
This network shows the impact of Data Science for Business: What You Need to Know about Data Mining and Data-Analytic Thinking. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the Data Science for Business: What You Need to Know about Data Mining and Data-Analytic Thinking.
About Data Science for Business: What You Need to Know about Data Mining and Data-Analytic Thinking
This paper, published in 2013, received 383 indexed citations . Written by Foster Provost and Tom Fawcett covering the research area of Management Information Systems. It is primarily cited by scholars working on Management Information Systems (111 citations), Artificial Intelligence (89 citations), Information Systems (68 citations), Management Science and Operations Research (58 citations) and Marketing (45 citations).
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.
This paper is also available at doi.org/w73471307.