70 most recommended articles in Big Data space

15th Jul `14, 05:56 PM in Resources

This is a collection of 70 most recommended articles in Big Data landscape. The list is based on…

Baiju NT Contributor

This is a collection of 70 most recommended articles in Big Data landscape. The list is based on recommendations by leading websites, bloggers, big data community leaders/members and users of various social media channels. The articles are arranged in no particular order.

1. Why becoming a Data Scientist is NOT actually easier than you think

2. Big Data Beyond MapReduce: Google’s Big Data Papers

3. Difference between Data Scientist and Data Analyst

4. Machine Learning in 10 pictures

5. Big Data: A Practical Definition

6. Parallel Programming in the Age of Big Data

7. 9 Open Source Big Data Technologies to Watch

8. The Pathologies of Big Data

9. 10 surprising Machine Learning applications

10. Tapping into the power of Big Data

11. Hadoop Basics – Creating a MapReduce Program

12. 8 Real-World Big Data Deployments

13. The $30/hr Data Scientist

14. Reinventing Society In The Wake Of Big Data

15. 10 Trends Driving Big Data in Financial Services

16. Get Ready For Sensor-Driven Business Models

17. Can big data be racist?

18. Fill in the Blanks: Using Math to Turn Lo-Res Datasets Into Hi-Res Samples

19. Data scientists need their own GitHub. Here are four of the best options

20. How to Be Ready for Big Data

21. 7 Big Data Solutions Try To Reshape Healthcare

22. Getting started in Data Science: My thoughts [Trey Causey]

23. Big Data Causes Concern and Big Confusion

24. 5 Big Wishes For Big Data Deployments

25. When Astronomy Met Computer Science

26. “How do I become a Data Scientist?”

27. Equifax Eyes Are Watching YouBig Data Means Big Brother

28. How Big Data Brings BI, Predictive Analytics Together

29. Elusive Data Scientists Driving High Salaries

30. Big Data’s Surprising Uses: From Lady Gaga To CIA

31. How I made $500k with Machine Learning and High Frequency Trading

32. Microsoft’s Big Data Strategy: An Insider’s View

33. Deep Learning – How & Why Deep Learning Methods Work

34. A non-comprehensive list of awesome things other people did this year

35. Big Data Career Switch: 4 Key Points

36. Big Data Analytics Today Lets Businesses Play Moneyball

37. Why The R Programming Language Is Good For Business

38. What I learnt from 2 years of ‘Data Sciencing’

39. IBM And Big Data Disruption: Insider’s View

40. The Big Data Challenge: How to Develop a Winning Strategy

41. Data, data everywhere

42. You might be a Data Scientist if

43. Hadoop Creator Outlines the Future of Big Data Platform

44. NoSQL Vs. Hadoop: Big Data Spotlight At E2

45. Big Data Is Less About Size, And More About Freedom

46. Is Julia the Future for Big Data Analytics?

47. What is the Difference Between Artificial Intelligence, Machine Learning, Statistics, and Data Mining

48. Clouds, big data, and smart assets: Ten tech-enabled business trends to watch

49. How to Use Big Data to Stop Customer Churn

50. Five Things CIOs Should Know About Big Data

51. META: What Data Scientists are reading. And why.

52. This Data Scientist spent a year deep inside The New York Times. Here’s what he discovered

53. Big (Bad) Data

54. New to Data Science

55. The Big Data Landscape

56. Big Data Debate: Will Hadoop Become Dominant Platform?

57. How Python became the language of choice for Data Science

58. 10 Mistakes Enterprises Make in Big Data Projects

59. The real promise of big data: It’s changing the whole way humans will solve problems

60. Scientists set new speed record for big data

61. BlueKai Acquisition Validates that Customer Data is King

62. Why “Big Data” Is a Big Deal

63. How to find the bars that women love

64. Big Data: Are you ready for blast-off?

65. What Big-Data VCs are Sick of — and What They Really Want

66. 4 Ways to Actually Use Big Data

67. Big Data, Big Business, Big Brother?

68. Big Data’s Fading Bloom

69. Data Isn’t Just for the Big Guys Anymore

70. PayPal chief scientist on cracking the code for big data analytics