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What people want (and how to predict it)
Davenport, Thomas H.
;
Harris, Jeanne G.
- In:
MIT sloan management review
50
(
2008/09
)
2
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pp. 23-31
Persistent link: https://www.econbiz.de/10003807490
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The prediction lover's handbook
Davenport, Thomas H.
;
Harris, Jeanne G.
- In:
MIT sloan management review
50
(
2008/09
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2
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pp. 32-34
Persistent link: https://www.econbiz.de/10003807491
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How fast and flexible do you want your data, really?
Davenport, Thomas H.
;
Snabe, Jim Hagemann
- In:
MIT sloan management review
52
(
2010/11
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3
,
pp. 57-62
Persistent link: https://www.econbiz.de/10009008544
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How big data is different
Davenport, Thomas H.
;
Barth, Paul
;
Bean, Randy
- In:
MIT sloan management review
54
(
2012/13
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1
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pp. 43-46
Persistent link: https://www.econbiz.de/10009661392
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Just how smart are smart machines?
Davenport, Thomas H.
;
Kirby, Julia
- In:
MIT sloan management review
57
(
2015/2016
)
3
,
pp. 21-25
Persistent link: https://www.econbiz.de/10011457174
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What businesses can learn from sports analytics
Davenport, Thomas H.
- In:
MIT sloan management review
55
(
2013/14
)
4
,
pp. 10-13
Persistent link: https://www.econbiz.de/10010398889
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What Coronavirus reveals about our decision biases
Davenport, Thomas H.
- In:
MIT sloan management review
61
(
2020
)
4
,
pp. 79-81
Persistent link: https://www.econbiz.de/10012254683
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Rise of the strategy machines
Davenport, Thomas H.
- In:
MIT sloan management review
58
(
2016
)
1
,
pp. 29-30
Persistent link: https://www.econbiz.de/10011603170
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Can we solve AI's "trust problem"?
Davenport, Thomas H.
- In:
MIT sloan management review
60
(
2019
)
2
,
pp. 18-19
Persistent link: https://www.econbiz.de/10011980854
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Collaborate smarter, not harder
Cross, Rob
;
Davenport, Thomas H.
;
Gray, Peter
- In:
MIT sloan management review
61
(
2019
)
1
,
pp. 20-28
Persistent link: https://www.econbiz.de/10012107493
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