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{ "item_title" : "Analyzing the Analyzers", "item_author" : [" Harlan Harris", "Sean Murphy", "Marck Vaisman "], "item_description" : "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", "item_img_path" : "https://covers1.booksamillion.com/covers/bam/1/44/937/176/1449371760_b.jpg", "price_data" : { "retail_price" : "9.99", "online_price" : "9.99", "our_price" : "9.99", "club_price" : "9.99", "savings_pct" : "0", "savings_amt" : "0.00", "club_savings_pct" : "0", "club_savings_amt" : "0.00", "discount_pct" : "10", "store_price" : "" } }
Analyzing the Analyzers|Harlan Harris

Analyzing the Analyzers

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Overview

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 Researchers
  • Cases in miscommunication between data scientists and organizations looking to hire
  • Why "T-shaped" data scientists have an advantage in breadth and depth of skills
  • How organizations can apply the survey results to identify, train, integrate, team up, and promote data scientists

This item is Non-Returnable

Details

  • ISBN-13: 9781449371760
  • ISBN-10: 1449371760
  • Publisher: O'Reilly Media
  • Publish Date: July 2013
  • Dimensions: 9 x 6 x 0.08 inches
  • Shipping Weight: 0.15 pounds
  • Page Count: 38

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