Isbn: 9781449371760 - analyzing the analyzers: an introspective survey of data scientists and their work (19 resultados)

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Paperback. Condición: New. 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.…

Paperback or Softback. Condición: New. Analyzing the Analyzers: An Introspective Survey of Data Scientists and Their Work. Book.

Condición: Good. Former library copy. Pages intact with minimal writing/highlighting. The binding may be loose and creased. Dust jackets/supplements are not included. Includes library markings. Stock photo provided. Product includes identifying sticker. Better World Books: Buy Books. Do Good.

PAP. Condición: New. New Book. Shipped from UK. Established seller since 2000.

Condición: New. Num Pages: 80 pages, Illustrations. BIC Classification: UNC. Category: (XV) Technical / Manuals. Dimension: 230 x 166 x 5. Weight in Grams: 134. . 2013. 1st Edition. Paperback. . . . .

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Paperback. Condición: Brand New. 40 pages. 9.00x6.00x0.25 inches. In Stock.

Condición: New. Num Pages: 80 pages, Illustrations. BIC Classification: UNC. Category: (XV) Technical / Manuals. Dimension: 230 x 166 x 5. Weight in Grams: 134. . 2013. 1st Edition. Paperback. . . . . Books ship from the US and Ireland.

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Condición: New. pp. 80.

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Taschenbuch. Condición: Neu. Neuware - Despite the excitement around 'data science,' 'big data,' and 'analytics,' the ambiguity of these terms has led to poor communication between data scientists and organizations seeking their help. In this report, authors Harlan Harris, Sean Murphy, and Marck Vaisman examine their survey of several hundred data science practitioners in mid-2012, when they asked respondents how they viewed their skills, careers, and experiences with prospective employers. The results are striking.Based on the survey data, the authors found that data scientists today can be clustered into four subgroups, each with a different mix of skillsets. Their purpose is to identify a new, more precise vocabulary for data science roles, teams, and career paths.This report describes:Four data scientist clusters: Data Businesspeople, Data Creatives, Data Developers, and Data ResearchersCases in miscommunication between data scientists and organizations looking to hireWhy 'T-shaped' data scientists have an advantage in breadth and depth of skillsHow organizations can apply the survey results to identify, train, integrate, team up, and promote data scientists.…

Paperback. Condición: New. 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.…

Paperback. Condición: Brand New. 40 pages. 9.00x6.00x0.25 inches. In Stock. This item is printed on demand.

Condición: Gut. Zustand: Gut | Sprache: Englisch | Produktart: Bücher | Keine Beschreibung verfügbar.

Condición: Hervorragend. Zustand: Hervorragend | Sprache: Englisch | Produktart: Bücher | Keine Beschreibung verfügbar.