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  3. Datafangst og dataanalyse

Analyzing the Analyzers

- An Introspective Survey of Data Scientists and Their Work
Af: Harlan Harris Engelsk Paperback

Analyzing the Analyzers

- An Introspective Survey of Data Scientists and Their Work
Af: Harlan Harris Engelsk Paperback
Tjek vores konkurrenters priser
There has been intense excitement in recent years around activities labeled "data science," "big data," and "analytics." However, the lack of clarity around these terms and, particularly, around the skill sets and capabilities of their practitioners has led to inefficient communication between "data scientists" and the organizations requiring their services. This lack of clarity has frequently led to missed opportunities. To address this issue, we surveyed several hundred practitioners via the Web to explore the varieties of skills, experiences, and viewpoints in the emerging data science community. We used dimensionality reduction techniques to divide potential data scientists into five categories based on their self-ranked skill sets (Statistics, Math/Operations Research, Business, Programming, and Machine Learning/Big Data), and four categories based on their self-identification (Data Researchers, Data Businesspeople, Data Engineers, and Data Creatives). Further examining the respondents based on their division into these categories provided additional insights into the types of professional activities, educational background, and even scale of data used by different types of Data Scientists. In this report, we combine our results with insights and data from others to provide a better understanding of the diversity of practitioners, and to argue for the value of clearer communication around roles, teams, and careers.
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There has been intense excitement in recent years around activities labeled "data science," "big data," and "analytics." However, the lack of clarity around these terms and, particularly, around the skill sets and capabilities of their practitioners has led to inefficient communication between "data scientists" and the organizations requiring their services. This lack of clarity has frequently led to missed opportunities. To address this issue, we surveyed several hundred practitioners via the Web to explore the varieties of skills, experiences, and viewpoints in the emerging data science community. We used dimensionality reduction techniques to divide potential data scientists into five categories based on their self-ranked skill sets (Statistics, Math/Operations Research, Business, Programming, and Machine Learning/Big Data), and four categories based on their self-identification (Data Researchers, Data Businesspeople, Data Engineers, and Data Creatives). Further examining the respondents based on their division into these categories provided additional insights into the types of professional activities, educational background, and even scale of data used by different types of Data Scientists. In this report, we combine our results with insights and data from others to provide a better understanding of the diversity of practitioners, and to argue for the value of clearer communication around roles, teams, and careers.
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Se mere i:
Produktdetaljer
Sprog: Engelsk
Sider: 80
ISBN-13: 9781449371760
Indbinding: Paperback
Udgave:
ISBN-10: 1449371760
Kategori: Datafangst og dataanalyse
Udg. Dato: 23 jul 2013
Længde: 5mm
Bredde: 166mm
Højde: 230mm
Forlag: O'Reilly Media
Oplagsdato: 23 jul 2013
Forfatter(e): Harlan Harris
Forfatter(e) Harlan Harris

Kategori Datafangst og dataanalyse

ISBN-13 9781449371760

Sprog Engelsk

Indbinding Paperback

Sider 80

Udgave

Længde 5mm

Bredde 166mm

Højde 230mm

Udg. Dato 23 jul 2013

Oplagsdato 23 jul 2013

Forlag O'Reilly Media

Kategori sammenhænge