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Autor(en): 
  • Jugulum Rajesh
  • Common Data Sense for Professionals: A Process-Oriented Approach for Data-Science Projects 
     

    (Buch)
    Dieser Artikel gilt, aufgrund seiner Grösse, beim Versand als 3 Artikel!


    Übersicht

    Auf mobile öffnen
     
    Lieferstatus:   Auf Bestellung (Lieferzeit unbekannt)
    Veröffentlichung:  Januar 2022  
    Genre:  Wirtschaft / Recht 
     
    Account Risk / analytical software tools / Bell Shaped Curve / Better Problem Statement / BUSINESS & ECONOMICS / Information Management / BUSINESS & ECONOMICS / Management / BUSINESS & ECONOMICS / Management Science / BUSINESS & ECONOMICS / Marketing / Research
    ISBN:  9780367760489 
    EAN-Code: 
    9780367760489 
    Verlag:  Taylor and Francis 
    Einband:  Kartoniert  
    Sprache:  English  
    Dimensionen:  H 229 mm / B 152 mm / D  
    Gewicht:  680 gr 
    Seiten:  100 
    Illustration:  schwarz-weiss Illustrationen, Zeichnungen, schwarz-weiss 
    Bewertung: Titel bewerten / Meinung schreiben
    Inhalt:
    Data is an intrinsic part of our daily lives. Everything we do is a data point. Many of these data points are recorded with the intent to help us lead more efficient lives. We have apps that track our workouts, sleep, food intake, and personal finance. We use the data to make changes to our lives based on goals we have set for ourselves. Businesses use vast collections of data to determine strategy and marketing. Data scientists take data, analyze it, and create models to help solve problems. You may have heard of companies having data management teams or chief information officers (CIOs) or chief data officers (CDOs), etc. They are all people who work with data, but their function is more related to vetting data and preparing it for use by data scientists. The jump from personal data usage for self-betterment to mass data analysis for business process improvement often feels bigger to us than it is. In turn, we often think big data analysis requires tools held only by advanced degree holders. Although advanced degrees are certainly valuable, this book illustrates how it is not a requirement to adequately run a data science project. Because we are all already data users, with some simple strategies and exposure to basic analytical software programs, anyone who has the proper tools and determination can solve data science problems. The process presented in this book will help empower individuals to work on and solve data-related challenges. The goal of this book is to provide a step-by-step guide to the data science process so that you can feel confident in leading your own data science project. To aid with clarity and understanding, the author presents a fictional restaurant chain to use as a case study, illustrating how the various topics discussed can be applied. Essentially, this book helps traditional businesspeople solve data-related problems on their own without any hesitation or fear. The powerful methods are presented in the form of conversations, examples, and case studies. The conversational style is engaging and provides clarity.

      



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