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Monday, May 18, 2015 Big Data By Sathish Yellanki Slide No : 1
A Very Big Question To Answer
What is Big Data?
Formal Definitions of Big Data
Big Data is The Frontier of A Firm's Ability To
Store, Process, Access (SPA)
All The Data it Needs To
Operate Effectively
...
Big Data in General is Defined As
High Volume, Velocity And Variety
Information Assets That Demands
Cost-Effective
Innovat...
Big Data is Data That Exceeds The
Processing Capacity of Conventional Database
Systems
The Data is Too Big, Moves Too Fast...
Big Data is The Data Characterized By 3 Attributes
Volume
Variety
Velocity
Definition 04
…IBM
Big Data is Data Characterized By 4 Key Attributes
Volume
Variety
Velocity
Value
Definition 05
…Oracle
How An Analyst, Designer, Administrator,
Architect And Developer Should See The Big Data
By Complexity of Storage Size
By Criticality of Backup And Recovery
By Challenge of Search And Optimizing Time
By Variatio...
How To Build An Idea Practically About Big Data?
Question
What is The Size That We Need To Fit A Single
Character of Data?
Answer
One Byte
Situational Question
Do You Have...
Question
What is The Size That We Need To Fit A Single Digit
of a Number?
Answer
Two Bytes
Situational Question
Do You Hav...
Question
What is The Maximum Size of Data Storage in A
MS-Word File?
Answer
32 MB
Situational Question
Do You Have Your Da...
Question
What is The Maximum Size of Data Storage in A
Data File of Oracle?
Answer
Block Size Maximum Datafile File Size
2...
Finally How To Identify The “Big Data” Limit?
• Big Data is Something When it is Unable To Fit
into The RAM.
• Small Data is Something When it Can Fit into
The RAM.
Let Us Have A Symbolic Reference For Clarity
Byte : One Grain of Rice
Byte : One Grain of Rice
Kilobyte : Cup of Rice
Byte : One Grain of Rice
Kilobyte : Cup of Rice
Megabyte : 8 Bags of Rice
Byte : One Grain of Rice
Kilobyte : Cup of Rice
Megabyte : 8 Bags of Rice
Gigabyte : 3 Semi Trucks
Byte : One Grain of Rice
Kilobyte : Cup of Rice
Megabyte : 8 Bags of Rice
Gigabyte : 3 Semi Trucks
Terabyte : 2 Container ...
Byte : One Grain of Rice
Kilobyte : Cup of Rice
Megabyte : 8 Bags of Rice
Gigabyte : 3 Semi Trucks
Terabyte : 2 Container ...
Byte : One Grain of Rice
Kilobyte : Cup of Rice
Megabyte : 8 Bags of Rice
Gigabyte : 3 Semi Trucks
Terabyte : 2 Container ...
Byte : One Grain of Rice
Kilobyte : Cup of Rice
Megabyte : 8 Bags of Rice
Gigabyte : 3 Semi Trucks
Terabyte : 2 Container ...
Byte : One Grain of Rice
Kilobyte : Cup of Rice
Megabyte : 8 Bags of Rice
Gigabyte : 3 Semi Trucks
Terabyte : 2 Container ...
Area of Application By Memory Size
Byte : One Grain of Rice
Kilobyte : Cup of Rice
Megabyte : 8 Bags of Rice
Gigabyte : 3 Semi Trucks
Terabyte : 2 Container ...
Byte : One Grain of Rice
Kilobyte : Cup of Rice
Megabyte : 8 Bags of Rice
Gigabyte : 3 Semi Trucks
Terabyte : 2 Container ...
Byte : One Grain of Rice
Kilobyte : Cup of Rice
Megabyte : 8 Bags of Rice
Gigabyte : 3 Semi Trucks
Terabyte : 2 Container ...
Byte : One Grain of Rice
Kilobyte : Cup of Rice
Megabyte : 8 Bags of Rice
Gigabyte : 3 Semi Trucks
Terabyte : 2 Container ...
Byte : One Grain of Rice
Kilobyte : Cup of Rice
Megabyte : 8 Bags of Rice
Gigabyte : 3 Semi Trucks
Terabyte : 2 Container ...
What is The Key Parameter To Be Considered in
Big Data?
• Big Data is Not About The
Size of The Data.
• Big Data is About The
Value Within The Data.
So, What is The Level of value?
When Big Data Will Be Valued?
Market Intelligence?
Market Intelligence?
Business Intelligence?
Market Intelligence?
Business Intelligence?
Secret Intelligence?
Market Intelligence?
Business Intelligence?
Secret Intelligence?
Forensic Intelligence?
Market Intelligence?
Business Intelligence?
Secret Intelligence?
Forensic Intelligence?
Medical Intelligence?
Market Intelligence?
Business Intelligence?
Secret Intelligence?
Forensic Intelligence?
Space Intelligence?
Medical Intell...
Big Data
Monday, May 18, 2015 Big Data By Sathish Yellanki Slide No : 45
A Big Question For The Next Generation
Answer
Yes, Our Society And System is Leaving Behind A
Digital Footprint.
Monday, May 18, 2015 Big Data By Sathish Yellank...
Monday, May 18, 2015 Big Data By Sathish Yellanki Slide No : 47
A Big Question For The Community of Humans
Monday, May 18, 2015 Big Data By Sathish Yellanki Slide No : 48
Answer
Majority of The Human Race is Living Online.
Questi...
Monday, May 18, 2015 Big Data By Sathish Yellanki Slide No : 49
Answer
Majority of The Human Race is Living Online.
Questi...
Monday, May 18, 2015 Big Data By Sathish Yellanki Slide No : 50
Answer
Majority of The Human Race is Living Online.
Questi...
Monday, May 18, 2015 Big Data By Sathish Yellanki Slide No : 51
Answer
Majority of The Human Race is Living Online.
Questi...
Monday, May 18, 2015 Big Data By Sathish Yellanki Slide No : 52
Answer
Majority of The Human Race is Living Online.
Questi...
Monday, May 18, 2015 Big Data By Sathish Yellanki Slide No : 53
Answer
Majority of The Human Race is Living Online.
Questi...
Monday, May 18, 2015 Big Data By Sathish Yellanki Slide No : 54
Answer
Majority of The Human Race is Living Online.
Questi...
Monday, May 18, 2015 Big Data By Sathish Yellanki Slide No : 55
Answer
Majority of The Human Race is Living Online.
Questi...
Monday, May 18, 2015 Big Data By Sathish Yellanki Slide No : 56
Answer
Majority of The Human Race is Living Online.
Questi...
Monday, May 18, 2015 Big Data By Sathish Yellanki Slide No : 57
Answer
Majority of The Human Race is Living Online.
Questi...
Monday, May 18, 2015 Big Data By Sathish Yellanki Slide No : 58
Answer
Majority of The Human Race is Living Online.
Questi...
Monday, May 18, 2015 Big Data By Sathish Yellanki Slide No : 59
A Big Question For The System Developers
Monday, May 18, 2015 Big Data By Sathish Yellanki Slide No : 60
Answer
Yes
Question
Are We Generating Huge Amounts of Data?
Monday, May 18, 2015 Big Data By Sathish Yellanki Slide No : 61
Question
What This Data is Actually Containing?
Answer
Dat...
Monday, May 18, 2015 Big Data By Sathish Yellanki Slide No : 62
Question
What This Data is Actually Containing?
Answer
Dat...
Monday, May 18, 2015 Big Data By Sathish Yellanki Slide No : 63
Answer
A Developer Should Develop The Ability To Hear
The ...
Monday, May 18, 2015 Big Data By Sathish Yellanki Slide No : 64
Are We Aware of The Big Challenge That is Ahead
Monday, May 18, 2015 Big Data By Sathish Yellanki Slide No : 65
Question
What is The Challenge We Will Face?
Answer
Unlock...
Monday, May 18, 2015 Big Data By Sathish Yellanki Slide No : 66
Question
What Are The Other Conversations We Should
Monito...
Monday, May 18, 2015 Big Data By Sathish Yellanki Slide No : 67
What Happens if We Can Listen To The Conversation
of The H...
Monday, May 18, 2015 Big Data By Sathish Yellanki Slide No : 68
• Move Towards The Unexpected Discoveries
• Re-Invent The ...
Monday, May 18, 2015 Big Data By Sathish Yellanki Slide No : 69
The Biggest Question Finally on Big Data
Monday, May 18, 2015 Big Data By Sathish Yellanki Slide No : 70
Shall We Mine The Data OR Mind The Data?
Does The Organiza...
Monday, May 18, 2015 Big Data By Sathish Yellanki Slide No : 71
So Finally Where To Start With Big Data?
Monday, May 18, 2015 Big Data By Sathish Yellanki Slide No : 72
Get Big
The Bulls Eye For Success Finally Lies in
By Start...
Monday, May 18, 2015 Big Data By Sathish Yellanki Slide No : 73
Where I Should Focus For My Success?
Monday, May 18, 2015 Big Data By Sathish Yellanki Slide No : 74
Focus on The Areas That Contradict
With Impact of
Business...
Monday, May 18, 2015 Big Data By Sathish Yellanki Slide No : 75
What is The Flow Chart of Big Data Analytics?
Monday, May 18, 2015 Big Data By Sathish Yellanki Slide No : 76
Start
Did it
Work?
Stop
Try Something Out of
The Business ...
Monday, May 18, 2015 Big Data By Sathish Yellanki Slide No : 77
Is Big Data is Really Big?
Monday, May 18, 2015 Big Data By Sathish Yellanki Slide No : 78
To Speak Frankly No
For The People Who Know How To Use
The...
Monday, May 18, 2015 Big Data By Sathish Yellanki Slide No : 79
What is The End Result if I Know How To Tame The
Big Data?
Monday, May 18, 2015 Big Data By Sathish Yellanki Slide No : 80
Big Data Simply Obliges All Your Needs
And
Looks And Execu...
Monday, May 18, 2015 Big Data By Sathish Yellanki Slide No : 81
Thank You See You Soon With Hadoop
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Bigdata presentation

  1. 1. Monday, May 18, 2015 Big Data By Sathish Yellanki Slide No : 1 A Very Big Question To Answer
  2. 2. What is Big Data?
  3. 3. Formal Definitions of Big Data
  4. 4. Big Data is The Frontier of A Firm's Ability To Store, Process, Access (SPA) All The Data it Needs To Operate Effectively Make Decisions Reduce Risks Serve Customers Definition 01 …Forrester
  5. 5. Big Data in General is Defined As High Volume, Velocity And Variety Information Assets That Demands Cost-Effective Innovative Forms of Information Processing For Enhanced Insight And Decision Making Definition 02 …Gartner
  6. 6. Big Data is Data That Exceeds The Processing Capacity of Conventional Database Systems The Data is Too Big, Moves Too Fast, OR Doesn't Fit The Structures of Clients Database Architectures To Gain Value From This Data, The Client Must Choose An Alternative Way To Process it Definition 03 …O’Reilly
  7. 7. Big Data is The Data Characterized By 3 Attributes Volume Variety Velocity Definition 04 …IBM
  8. 8. Big Data is Data Characterized By 4 Key Attributes Volume Variety Velocity Value Definition 05 …Oracle
  9. 9. How An Analyst, Designer, Administrator, Architect And Developer Should See The Big Data
  10. 10. By Complexity of Storage Size By Criticality of Backup And Recovery By Challenge of Search And Optimizing Time By Variations of The Tools And Technologies By The Dynamism of Change And Scalability By The Resistance in Building The Man Power By The Speed of Research in Applying By The Variety of Data Formats That Arise By The Composition of Demanded Multiple Skillsets
  11. 11. How To Build An Idea Practically About Big Data?
  12. 12. Question What is The Size That We Need To Fit A Single Character of Data? Answer One Byte Situational Question Do You Have The Required Memory Size? Scenarios That May Arise • Yes, Then it is Small Data • No, Then it is Big Data As Per Your Requirement What To Do To Fit The Data When it is “NO” • Design And Develop Architecture For Big Data
  13. 13. Question What is The Size That We Need To Fit A Single Digit of a Number? Answer Two Bytes Situational Question Do You Have The Required Memory Size? Scenarios That May Arise • Yes, Then it is Small Data • No, Then it is Big Data As Per Your Requirement What To Do To Fit The Data When it is “NO” • Design And Develop Architecture For Big Data
  14. 14. Question What is The Maximum Size of Data Storage in A MS-Word File? Answer 32 MB Situational Question Do You Have Your Data Upto OR More Than 32 MB Scenarios That May Arise • Yes, Then it is Small Data • No, Then it is Big Data As Per Your Requirement What To Do To Fit The Data When it is “NO” • Design And Develop Architecture For Big Data
  15. 15. Question What is The Maximum Size of Data Storage in A Data File of Oracle? Answer Block Size Maximum Datafile File Size 2K 4194303 * 2K = 8 GB 4K 4194303 * 4K = 16 GB 8K 4194303 * 8K = 32 GB 16K 4194303 * 16K = 64 GB 32K 4194303 * 32K = 128 GB Block Size Maximum Datafile File Size 2k 4294967295 * 2K = 8 TB 4k 4294967295 * 4K = 16 TB 8k 4294967295 * 8K = 32 TB 16k 4294967295 * 16K = 64 TB 32k 4294967295 * 32K = 128 TB Big File Table Space Normal File Table Space
  16. 16. Finally How To Identify The “Big Data” Limit?
  17. 17. • Big Data is Something When it is Unable To Fit into The RAM. • Small Data is Something When it Can Fit into The RAM.
  18. 18. Let Us Have A Symbolic Reference For Clarity
  19. 19. Byte : One Grain of Rice
  20. 20. Byte : One Grain of Rice Kilobyte : Cup of Rice
  21. 21. Byte : One Grain of Rice Kilobyte : Cup of Rice Megabyte : 8 Bags of Rice
  22. 22. Byte : One Grain of Rice Kilobyte : Cup of Rice Megabyte : 8 Bags of Rice Gigabyte : 3 Semi Trucks
  23. 23. Byte : One Grain of Rice Kilobyte : Cup of Rice Megabyte : 8 Bags of Rice Gigabyte : 3 Semi Trucks Terabyte : 2 Container Ships
  24. 24. Byte : One Grain of Rice Kilobyte : Cup of Rice Megabyte : 8 Bags of Rice Gigabyte : 3 Semi Trucks Terabyte : 2 Container Ships Petabyte : Blankets Manhattan Area • Total 33.6 SQ MI (87 KM 2 ) • Land 22.8 SQ MI (59 KM 2 ) • Water 10.8 SQ MI (28 KM 2 ) 32% Population (2013) • Total 1,626,159 • Density 70,825.6/SQ MI (27,345.9/KM 2 )
  25. 25. Byte : One Grain of Rice Kilobyte : Cup of Rice Megabyte : 8 Bags of Rice Gigabyte : 3 Semi Trucks Terabyte : 2 Container Ships Petabyte : Blankets Manhattan Exabyte : Blankets West Coast States
  26. 26. Byte : One Grain of Rice Kilobyte : Cup of Rice Megabyte : 8 Bags of Rice Gigabyte : 3 Semi Trucks Terabyte : 2 Container Ships Petabyte : Blankets Manhattan Exabyte : Blankets West Coast States Zettabyte : Fills The Pacific Ocean Area of 165,200,000 KM²
  27. 27. Byte : One Grain of Rice Kilobyte : Cup of Rice Megabyte : 8 Bags of Rice Gigabyte : 3 Semi Trucks Terabyte : 2 Container Ships Petabyte : Blankets Manhattan Exabyte : Blankets West Coast States Zettabyte : Fills The Pacific Ocean Yottabyte : A Earth Size Rice Ball! Surface Area : 510,072,000 KM² Radius : 6,371 KM Volume : 1.08321×1012 KM3
  28. 28. Area of Application By Memory Size
  29. 29. Byte : One Grain of Rice Kilobyte : Cup of Rice Megabyte : 8 Bags of Rice Gigabyte : 3 Semi Trucks Terabyte : 2 Container Ships Petabyte : Blankets Manhattan Exabyte : Blankets West Coast States Zettabyte : Fills The Pacific Ocean Yottabyte : A Earth Size Rice Ball! Hobbyist
  30. 30. Byte : One Grain of Rice Kilobyte : Cup of Rice Megabyte : 8 Bags of Rice Gigabyte : 3 Semi Trucks Terabyte : 2 Container Ships Petabyte : Blankets Manhattan Exabyte : Blankets West Coast States Zettabyte : Fills The Pacific Ocean Yottabyte : A Earth Size Rice Ball! Hobbyist Desktop
  31. 31. Byte : One Grain of Rice Kilobyte : Cup of Rice Megabyte : 8 Bags of Rice Gigabyte : 3 Semi Trucks Terabyte : 2 Container Ships Petabyte : Blankets Manhattan Exabyte : Blankets West Coast States Zettabyte : Fills The Pacific Ocean Yottabyte : A Earth Size Rice Ball! Hobbyist Desktop Internet
  32. 32. Byte : One Grain of Rice Kilobyte : Cup of Rice Megabyte : 8 Bags of Rice Gigabyte : 3 Semi Trucks Terabyte : 2 Container Ships Petabyte : Blankets Manhattan Exabyte : Blankets West Coast States Zettabyte : Fills The Pacific Ocean Yottabyte : A Earth Size Rice Ball! Big Data
  33. 33. Byte : One Grain of Rice Kilobyte : Cup of Rice Megabyte : 8 Bags of Rice Gigabyte : 3 Semi Trucks Terabyte : 2 Container Ships Petabyte : Blankets Manhattan Exabyte : Blankets West Coast States Zettabyte : Fills The Pacific Ocean Yottabyte : A Earth Size Rice Ball! Hobbyist Desktop Internet Big Data Who Knows?
  34. 34. What is The Key Parameter To Be Considered in Big Data?
  35. 35. • Big Data is Not About The Size of The Data. • Big Data is About The Value Within The Data.
  36. 36. So, What is The Level of value?
  37. 37. When Big Data Will Be Valued?
  38. 38. Market Intelligence?
  39. 39. Market Intelligence? Business Intelligence?
  40. 40. Market Intelligence? Business Intelligence? Secret Intelligence?
  41. 41. Market Intelligence? Business Intelligence? Secret Intelligence? Forensic Intelligence?
  42. 42. Market Intelligence? Business Intelligence? Secret Intelligence? Forensic Intelligence? Medical Intelligence?
  43. 43. Market Intelligence? Business Intelligence? Secret Intelligence? Forensic Intelligence? Space Intelligence? Medical Intelligence?
  44. 44. Big Data
  45. 45. Monday, May 18, 2015 Big Data By Sathish Yellanki Slide No : 45 A Big Question For The Next Generation
  46. 46. Answer Yes, Our Society And System is Leaving Behind A Digital Footprint. Monday, May 18, 2015 Big Data By Sathish Yellanki Slide No : 46 Question Are We Going To Be A Digital World?
  47. 47. Monday, May 18, 2015 Big Data By Sathish Yellanki Slide No : 47 A Big Question For The Community of Humans
  48. 48. Monday, May 18, 2015 Big Data By Sathish Yellanki Slide No : 48 Answer Majority of The Human Race is Living Online. Question Where Are We Living And Spending Time Today? We All Are Digitally And Virtually Expressing Our
  49. 49. Monday, May 18, 2015 Big Data By Sathish Yellanki Slide No : 49 Answer Majority of The Human Race is Living Online. Question Where Are We Living And Spending Time Today? We All Are Digitally And Virtually Expressing Our • Attitudes
  50. 50. Monday, May 18, 2015 Big Data By Sathish Yellanki Slide No : 50 Answer Majority of The Human Race is Living Online. Question Where Are We Living And Spending Time Today? We All Are Digitally And Virtually Expressing Our • Attitudes • Likes And Dislikes
  51. 51. Monday, May 18, 2015 Big Data By Sathish Yellanki Slide No : 51 Answer Majority of The Human Race is Living Online. Question Where Are We Living And Spending Time Today? We All Are Digitally And Virtually Expressing Our • Attitudes • Likes And Dislikes • Our Opinions
  52. 52. Monday, May 18, 2015 Big Data By Sathish Yellanki Slide No : 52 Answer Majority of The Human Race is Living Online. Question Where Are We Living And Spending Time Today? We All Are Digitally And Virtually Expressing Our • Attitudes • Likes And Dislikes • Our Opinions • Perspectives
  53. 53. Monday, May 18, 2015 Big Data By Sathish Yellanki Slide No : 53 Answer Majority of The Human Race is Living Online. Question Where Are We Living And Spending Time Today? We All Are Digitally And Virtually Expressing Our • Attitudes • Likes And Dislikes • Our Opinions • Perspectives • Happiness And Sorrow
  54. 54. Monday, May 18, 2015 Big Data By Sathish Yellanki Slide No : 54 Answer Majority of The Human Race is Living Online. Question Where Are We Living And Spending Time Today? We All Are Digitally And Virtually Expressing Our • Attitudes • Likes And Dislikes • Our Opinions • Perspectives • Happiness And Sorrow • Responsibilities And Rights
  55. 55. Monday, May 18, 2015 Big Data By Sathish Yellanki Slide No : 55 Answer Majority of The Human Race is Living Online. Question Where Are We Living And Spending Time Today? We All Are Digitally And Virtually Expressing Our • Attitudes • Likes And Dislikes • Our Opinions • Perspectives • Happiness And Sorrow • Responsibilities And Rights • Governance
  56. 56. Monday, May 18, 2015 Big Data By Sathish Yellanki Slide No : 56 Answer Majority of The Human Race is Living Online. Question Where Are We Living And Spending Time Today? We All Are Digitally And Virtually Expressing Our • Attitudes • Likes And Dislikes • Our Opinions • Perspectives • Governance • Happiness And Sorrow • Responsibilities And Rights • Strategies And Standards
  57. 57. Monday, May 18, 2015 Big Data By Sathish Yellanki Slide No : 57 Answer Majority of The Human Race is Living Online. Question Where Are We Living And Spending Time Today? We All Are Digitally And Virtually Expressing Our • Attitudes • Likes And Dislikes • Our Opinions • Perspectives • Happiness And Sorrow • Responsibilities And Rights • Governance • Strategies And Standards • Intelligence And Implementation
  58. 58. Monday, May 18, 2015 Big Data By Sathish Yellanki Slide No : 58 Answer Majority of The Human Race is Living Online. Question Where Are We Living And Spending Time Today? We All Are Digitally And Virtually Expressing Our • Attitudes • Likes And Dislikes • Our Opinions • Perspectives • Happiness And Sorrow • Responsibilities And Rights • Governance • Strategies And Standards • Intelligence And Implementation • Research And Application
  59. 59. Monday, May 18, 2015 Big Data By Sathish Yellanki Slide No : 59 A Big Question For The System Developers
  60. 60. Monday, May 18, 2015 Big Data By Sathish Yellanki Slide No : 60 Answer Yes Question Are We Generating Huge Amounts of Data?
  61. 61. Monday, May 18, 2015 Big Data By Sathish Yellanki Slide No : 61 Question What This Data is Actually Containing? Answer Data Integrated With A Lot of Information. Information in Association With A Lot of Noise.
  62. 62. Monday, May 18, 2015 Big Data By Sathish Yellanki Slide No : 62 Question What This Data is Actually Containing? Answer Data Integrated With A Lot of Information. Information in Association With A Lot of Noise. Data IntelligentSystem
  63. 63. Monday, May 18, 2015 Big Data By Sathish Yellanki Slide No : 63 Answer A Developer Should Develop The Ability To Hear The Signal From The Noise. Catching The Exact Signal For The Analysis And Research is Considered As The Key. Question What Ability The Developers Should Develop? Intelligent System
  64. 64. Monday, May 18, 2015 Big Data By Sathish Yellanki Slide No : 64 Are We Aware of The Big Challenge That is Ahead
  65. 65. Monday, May 18, 2015 Big Data By Sathish Yellanki Slide No : 65 Question What is The Challenge We Will Face? Answer Unlock The Human Conversation That is Taking Place Around Us.
  66. 66. Monday, May 18, 2015 Big Data By Sathish Yellanki Slide No : 66 Question What Are The Other Conversations We Should Monitor? Answer • The Human Machine Interaction And Interdependency • The Ability To Make Machines More Expertise in Managing The Failures OR if Possible Avoid The Failure • The Ability To Achieve The Super User Friendliness Architectures • Achieve Systems That Can Operate As Per The Thought of The Humans
  67. 67. Monday, May 18, 2015 Big Data By Sathish Yellanki Slide No : 67 What Happens if We Can Listen To The Conversation of The Humans Around?
  68. 68. Monday, May 18, 2015 Big Data By Sathish Yellanki Slide No : 68 • Move Towards The Unexpected Discoveries • Re-Invent The Failed Prophesies in Science And Technology • Analyze The Systems With More Deeper In- Sight • Cross Question The Process For Greater Success • Identify And Correct The Failures At The Early Stages • Report The System Break Ups At The Earliest Than Expected • Prevent a Total Failure of The System
  69. 69. Monday, May 18, 2015 Big Data By Sathish Yellanki Slide No : 69 The Biggest Question Finally on Big Data
  70. 70. Monday, May 18, 2015 Big Data By Sathish Yellanki Slide No : 70 Shall We Mine The Data OR Mind The Data? Does The Organizations And People Know What They Have To Do With Data What They Have With Them? No, Most People Do Not Know What To Do With All The Data They Already Have… • First We Should Mind The Data, Then Mine The Data, Then Mind The Data Then Mine The Data, Then Mind The Data Then Mine The Data…
  71. 71. Monday, May 18, 2015 Big Data By Sathish Yellanki Slide No : 71 So Finally Where To Start With Big Data?
  72. 72. Monday, May 18, 2015 Big Data By Sathish Yellanki Slide No : 72 Get Big The Bulls Eye For Success Finally Lies in By Starting Small
  73. 73. Monday, May 18, 2015 Big Data By Sathish Yellanki Slide No : 73 Where I Should Focus For My Success?
  74. 74. Monday, May 18, 2015 Big Data By Sathish Yellanki Slide No : 74 Focus on The Areas That Contradict With Impact of Business System Process Methodology
  75. 75. Monday, May 18, 2015 Big Data By Sathish Yellanki Slide No : 75 What is The Flow Chart of Big Data Analytics?
  76. 76. Monday, May 18, 2015 Big Data By Sathish Yellanki Slide No : 76 Start Did it Work? Stop Try Something Out of The Business Data YESNO YES
  77. 77. Monday, May 18, 2015 Big Data By Sathish Yellanki Slide No : 77 Is Big Data is Really Big?
  78. 78. Monday, May 18, 2015 Big Data By Sathish Yellanki Slide No : 78 To Speak Frankly No For The People Who Know How To Use The Concept And Credits of The Big Data Big Data is Not Big
  79. 79. Monday, May 18, 2015 Big Data By Sathish Yellanki Slide No : 79 What is The End Result if I Know How To Tame The Big Data?
  80. 80. Monday, May 18, 2015 Big Data By Sathish Yellanki Slide No : 80 Big Data Simply Obliges All Your Needs And Looks And Executes Like Smart Data
  81. 81. Monday, May 18, 2015 Big Data By Sathish Yellanki Slide No : 81 Thank You See You Soon With Hadoop

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