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Data Science and Big Data Analytics: Discovering, Analyzing, Visualizing and Presenting Data

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Data Science and Big Data Analytics is about harnessing the power of data for new insights. The book covers the breadth of activities and methods and tools that Data Scientists use. The content focuses on concepts, principles and practical applications that are applicable to any industry and technology environment, and the learning is supported and explained with examples Data Science and Big Data Analytics is about harnessing the power of data for new insights. The book covers the breadth of activities and methods and tools that Data Scientists use. The content focuses on concepts, principles and practical applications that are applicable to any industry and technology environment, and the learning is supported and explained with examples that you can replicate using open-source software. This book will help you: Become a contributor on a data science team Deploy a structured lifecycle approach to data analytics problems Apply appropriate analytic techniques and tools to analyzing big data Learn how to tell a compelling story with data to drive business action Prepare for EMC Proven Professional Data Science Certification Corresponding data sets are available at www.wiley.com/go/9781118876138. Get started discovering, analyzing, visualizing, and presenting data in a meaningful way today!


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Data Science and Big Data Analytics is about harnessing the power of data for new insights. The book covers the breadth of activities and methods and tools that Data Scientists use. The content focuses on concepts, principles and practical applications that are applicable to any industry and technology environment, and the learning is supported and explained with examples Data Science and Big Data Analytics is about harnessing the power of data for new insights. The book covers the breadth of activities and methods and tools that Data Scientists use. The content focuses on concepts, principles and practical applications that are applicable to any industry and technology environment, and the learning is supported and explained with examples that you can replicate using open-source software. This book will help you: Become a contributor on a data science team Deploy a structured lifecycle approach to data analytics problems Apply appropriate analytic techniques and tools to analyzing big data Learn how to tell a compelling story with data to drive business action Prepare for EMC Proven Professional Data Science Certification Corresponding data sets are available at www.wiley.com/go/9781118876138. Get started discovering, analyzing, visualizing, and presenting data in a meaningful way today!

56 review for Data Science and Big Data Analytics: Discovering, Analyzing, Visualizing and Presenting Data

  1. 4 out of 5

    Matt

    A good, broad textbook on data analysis and presentation in R, with introductory modelling techniques including regression, classification, clustering, association rule mining, and time series methods. Together with An Introduction to Statistical Learning with Applications in R by James et al., I'd recommend it to anyone aspiring to do quantitative research, be it data science, business/finance/economics, etc. A good, broad textbook on data analysis and presentation in R, with introductory modelling techniques including regression, classification, clustering, association rule mining, and time series methods. Together with An Introduction to Statistical Learning with Applications in R by James et al., I'd recommend it to anyone aspiring to do quantitative research, be it data science, business/finance/economics, etc.

  2. 4 out of 5

    Zach

    While this is a nice intro into machine learning in R, I think Hands-on Machine Learning with sklearn takes a much better approach (although it's in python). The code and data is accessible through github and there's an emphasis on theory rather than strictly formulas. While this is a nice intro into machine learning in R, I think Hands-on Machine Learning with sklearn takes a much better approach (although it's in python). The code and data is accessible through github and there's an emphasis on theory rather than strictly formulas.

  3. 5 out of 5

    David

    Great overview and enough detail of analytics models. Just the book I was looking for to go little deeper on understanding the analytical models (for non-data scientist)

  4. 5 out of 5

    Chris Finn

  5. 4 out of 5

    مشاعل

  6. 5 out of 5

    Louis

  7. 5 out of 5

    Jill Heinbigner

  8. 5 out of 5

    Suganya

  9. 4 out of 5

    Philip

  10. 5 out of 5

    John McKeever

  11. 4 out of 5

    Cyrille Savelief

  12. 5 out of 5

    Roel Castelein

  13. 4 out of 5

    Diego

  14. 5 out of 5

    Merin

  15. 5 out of 5

    Meher Ravali

  16. 4 out of 5

    Naveen

  17. 5 out of 5

    Wojtek Ptak

  18. 4 out of 5

    John

  19. 5 out of 5

    Srinivas

  20. 5 out of 5

    Nazmul Ahmed Noyon

  21. 5 out of 5

    Lyner Lim

  22. 5 out of 5

    Shathahir

  23. 4 out of 5

    Leonkap

  24. 5 out of 5

    Diego Montoliu

  25. 5 out of 5

    ساره خالد

  26. 5 out of 5

    Aparna

  27. 5 out of 5

    Dan Amrine

  28. 4 out of 5

    Diego Sarracino

  29. 4 out of 5

    Ryan Wood

  30. 4 out of 5

    John

  31. 4 out of 5

    Fg

  32. 5 out of 5

    Raul Zavala

  33. 5 out of 5

    Billy

  34. 5 out of 5

    Bhavuk

  35. 5 out of 5

    Milena Georgieva

  36. 5 out of 5

    Renilton

  37. 4 out of 5

    Sandeep

  38. 5 out of 5

    Rhian Thomas

  39. 5 out of 5

    Daniel

  40. 4 out of 5

    Jaron Clark

  41. 5 out of 5

    Fernando

  42. 4 out of 5

    Abbas

  43. 5 out of 5

    Abdallah Zayed

  44. 5 out of 5

    AlphaScale

  45. 4 out of 5

    María Gertrudis

  46. 4 out of 5

    Rafael Morales

  47. 5 out of 5

    Yang Zhang

  48. 5 out of 5

    Chris

  49. 5 out of 5

    Sandeep Singh

  50. 5 out of 5

    Mw

  51. 4 out of 5

    Tiago Henriques

  52. 5 out of 5

    Loice

  53. 5 out of 5

    Tunji Akinbami

  54. 4 out of 5

    Stefan

  55. 5 out of 5

    Aamir.khan

  56. 5 out of 5

    Manvendra Lodha

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