Big Data Week - Myths and Legends

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Nick Halstead

Presentation by Nick Halstead on some of the Myths around Big Data.

Technologie Business

NICK HALSTEAD, FOUNDER
DATASIFT, @NIK
Big Data
“Myths and Legends”
#BDW13
Thursday, 25 April 13

#BDW13
BIG DATASOCIAL DATA +
TV MONITORING POLITICAL TRACKING FINANCIAL FEEDS
#DATASIFT
Thursday, 25 April 13

#BDW13
BIG DATASOCIAL DATA +
TV MONITORING POLITICAL TRACKING FINANCIAL FEEDS1.5 BILLION ITEMS DAY
#DATASIFT
Thursday, 25 April 13

#BDW13
BIG DATASOCIAL DATA +
TV MONITORING POLITICAL TRACKING FINANCIAL FEEDS1.5 BILLION ITEMS DAY
1.5 PETABYTES OF STORAGE
#DATASIFT
Thursday, 25 April 13

#BDW13
BIG DATASOCIAL DATA +
TV MONITORING POLITICAL TRACKING FINANCIAL FEEDS1.5 BILLION ITEMS DAY
1.5 PETABYTES OF STORAGE
5000 CPU HADOOP CLUSTER #DATASIFT
Thursday, 25 April 13

Big Data
“Myths and Legends”
#BD13
Thursday, 25 April 13

BIG DATA PERCEPTION
#GOOGLE
I THOUGHT I WOULD ASK GOOGLE....
Thursday, 25 April 13

BIG DATA VENDOR “MYTHS”
Thursday, 25 April 13

1. YOU MUST BUY ALL OF THIS (for one job!)
#BDW13
Thursday, 25 April 13

2. HOW BIG IS “BIG”
Thursday, 25 April 13

20 PETABYTES IN EACH SEARCH INDEX REBULD (this was 2 years ago)
#BDW13
Thursday, 25 April 13

20 PETABYTES IN EACH SEARCH INDEX REBULD (this was 2 years ago)
900,000 SERVERS
#BDW13
Thursday, 25 April 13

#BDW13
3.2 BILLION LIKES AND COMMENTS PER DAY
Thursday, 25 April 13

#BDW13
3.2 BILLION LIKES AND COMMENTS PER DAY
OVER HALF A PETABYTE … EVERY 24 HOURS
Thursday, 25 April 13

150 MILLION SENSORS DELIVERING DATA 40 MILLION TIMES PER SECOND
#BDW13 #HADRON
Thursday, 25 April 13

150 MILLION SENSORS DELIVERING DATA 40 MILLION TIMES PER SECOND
10’s OF PETABYTES PER YEAR
#BDW13 #HADRON
Thursday, 25 April 13

A TYPICAL COMPANY
100 EMPLOYEES
Thursday, 25 April 13

A TYPICAL COMPANY
100 EMPLOYEES
10,000 CUSTOMERS
Thursday, 25 April 13

A TYPICAL COMPANY
100 EMPLOYEES
10,000 CUSTOMERS
25 DATABASES (customers, transactions, etc)
Thursday, 25 April 13

A TYPICAL COMPANY
100 EMPLOYEES
10,000 CUSTOMERS
1 MILLION TRANSACTIONS RECORDS
25 DATABASES (customers, transactions, etc)
Thursday, 25 April 13

A TYPICAL COMPANY
100 EMPLOYEES
10,000 CUSTOMERS
1 MILLION TRANSACTIONS RECORDS
5,000 BYTES PER TRANSACTION
25 DATABASES (customers, transactions, etc)
Thursday, 25 April 13

A TYPICAL HARDDRIVE
2000 GIGABYTES (2TB)
Thursday, 25 April 13

A TYPICAL HARDDRIVE
2000 GIGABYTES (2TB)
4000 GIGABYTES (4TB)
Thursday, 25 April 13

3. YOU NEED *LOTS* OF DATA SCIENTISTS
#DILBERT#BDW13
Thursday, 25 April 13

4. HOW BIG DATA IS USED
#BDW13
Thursday, 25 April 13

4. HOW BIG DATA IS USED
#BDW13
BANKING
Thursday, 25 April 13

4. HOW BIG DATA IS USED
#BDW13
BANKING
COMMUNICATIONS
Thursday, 25 April 13

4. HOW BIG DATA IS USED
#BDW13
BANKING
COMMUNICATIONS
GOVERNMENT
Thursday, 25 April 13

4. HOW BIG DATA IS USED
#BDW13
WEB LOGS 51%
Thursday, 25 April 13

4. HOW BIG DATA IS USED
#BDW13
WEB LOGS 51%
CLICK STREAM 35%
Thursday, 25 April 13

5. HADOOP GONE BAD
+
SQL
#BDW13 #HADOOPGONEBAD
Thursday, 25 April 13

RDBM - RELATIONAL DATABASE
#BDW13
Thursday, 25 April 13

RDBM - RELATIONAL DATABASE
NEEDS TO BE PRE-DEFINED
#BDW13
Thursday, 25 April 13

RDBM - RELATIONAL DATABASE
NEEDS TO BE PRE-DEFINED
REQUIRES INDEX TO PERFORM
#BDW13
Thursday, 25 April 13

RDBM - RELATIONAL DATABASE
NEEDS TO BE PRE-DEFINED
REQUIRES INDEX TO PERFORM
QUERIES ARE CONSTRAINED
#BDW13
Thursday, 25 April 13

MAP REDUCE
#MAPREDUCE#BDW13
Thursday, 25 April 13

MAP REDUCE
PROCESS CLOSE TO THE DATA
#MAPREDUCE#BDW13
Thursday, 25 April 13

MAP REDUCE
PROCESS CLOSE TO THE DATA
PARALLEL EXECUTION
#MAPREDUCE#BDW13
Thursday, 25 April 13

MAP REDUCE
PROCESS CLOSE TO THE DATA
PARALLEL EXECUTION
ANY TYPE OF ANALYSIS
#MAPREDUCE#BDW13
Thursday, 25 April 13

MAP REDUCE
PROCESS CLOSE TO THE DATA
PARALLEL EXECUTION
ANY TYPE OF ANALYSIS
HIDES DETAILS OFFAULT TOLERANCE, LOCALITY
AND LOAD BALANCING
#MAPREDUCE#BDW13
Thursday, 25 April 13

BIG DATA SCHEMA #NOSQL
HBASE
COLUMNS FILES
#BDW13
Thursday, 25 April 13

(QUICK ASIDE)
#SIDEBARThursday, 25 April 13

GOOGLE FILE SYSTEM (GFS) GOOGLE MAPREDUCE (GMR).
GOOGLE STARTED ALL THIS....
Thursday, 25 April 13

GOOGLE DREMEL
http://bit.ly/mS8QxX#BDW13
Thursday, 25 April 13

GOOGLE DREMEL
INTERACTIVE ANALYSIS
http://bit.ly/mS8QxX#BDW13
Thursday, 25 April 13

GOOGLE DREMEL
INTERACTIVE ANALYSIS
SCALE UP TO 10,000 SERVERS
http://bit.ly/mS8QxX#BDW13
Thursday, 25 April 13

GOOGLE DREMEL
INTERACTIVE ANALYSIS
SCALE UP TO 10,000 SERVERS
COLUMN STORAGE
http://bit.ly/mS8QxX#BDW13
Thursday, 25 April 13

OpenDremel
GOOGLE BIG QUERY
Google
Big Query
#BDW13
Thursday, 25 April 13

http://research.google.com/archive/spanner.html
GOOGLE SPANNER
#SPANNER #NEWSQL
Thursday, 25 April 13

http://research.google.com/archive/spanner.html
GOOGLE SPANNER
#SPANNER #NEWSQL
RELATIONAL DATABASE
Thursday, 25 April 13

http://research.google.com/archive/spanner.html
GOOGLE SPANNER
#SPANNER #NEWSQL
RELATIONAL DATABASE
GLOBALLY DISTRIBUTED
Thursday, 25 April 13

http://research.google.com/archive/spanner.html
GOOGLE SPANNER
#SPANNER #NEWSQL
RELATIONAL DATABASE
GLOBALLY DISTRIBUTED
USE GPS / TRUETIME
Thursday, 25 April 13

http://research.google.com/archive/spanner.html
GOOGLE SPANNER
#SPANNER #NEWSQL
RELATIONAL DATABASE
GLOBALLY DISTRIBUTED
USE GPS / TRUETIME
NO OPEN SOURCE EQUIVALENT
Thursday, 25 April 13

BIG DATA IS THE NEW OIL
Thursday, 25 April 13

NICK HALSTEAD, FOUNDER
HTTP://DATASIFT.COM
WE ARE HIRING!!
Thursday, 25 April 13

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Big Data Week - Myths and Legends

1. NICK HALSTEAD, FOUNDER DATASIFT, @NIK Big Data “Myths and Legends” #BDW13 Thursday, 25 April 13

2. #BDW13 BIG DATASOCIAL DATA + TV MONITORING POLITICAL TRACKING FINANCIAL FEEDS #DATASIFT Thursday, 25 April 13

3. #BDW13 BIG DATASOCIAL DATA + TV MONITORING POLITICAL TRACKING FINANCIAL FEEDS1.5 BILLION ITEMS DAY #DATASIFT Thursday, 25 April 13

4. #BDW13 BIG DATASOCIAL DATA + TV MONITORING POLITICAL TRACKING FINANCIAL FEEDS1.5 BILLION ITEMS DAY 1.5 PETABYTES OF STORAGE #DATASIFT Thursday, 25 April 13

5. #BDW13 BIG DATASOCIAL DATA + TV MONITORING POLITICAL TRACKING FINANCIAL FEEDS1.5 BILLION ITEMS DAY 1.5 PETABYTES OF STORAGE 5000 CPU HADOOP CLUSTER #DATASIFT Thursday, 25 April 13

6. Big Data “Myths and Legends” #BD13 Thursday, 25 April 13

7. BIG DATA PERCEPTION #GOOGLE I THOUGHT I WOULD ASK GOOGLE.... Thursday, 25 April 13

8. BIG DATA PERCEPTION #GOOGLE I THOUGHT I WOULD ASK GOOGLE.... Thursday, 25 April 13

9. BIG DATA PERCEPTION #GOOGLE I THOUGHT I WOULD ASK GOOGLE.... Thursday, 25 April 13

10. BIG DATA VENDOR “MYTHS” Thursday, 25 April 13

11. Thursday, 25 April 13

12. BIG DATA VENDOR “MYTHS” Thursday, 25 April 13

13. #BDW13 Thursday, 25 April 13

14. 1. YOU MUST BUY ALL OF THIS (for one job!) #BDW13 Thursday, 25 April 13

15. 2. HOW BIG IS “BIG” Thursday, 25 April 13

16. #BDW13 Thursday, 25 April 13

17. 20 PETABYTES IN EACH SEARCH INDEX REBULD (this was 2 years ago) #BDW13 Thursday, 25 April 13

18. 20 PETABYTES IN EACH SEARCH INDEX REBULD (this was 2 years ago) 900,000 SERVERS #BDW13 Thursday, 25 April 13

19. #BDW13 Thursday, 25 April 13

20. #BDW13 3.2 BILLION LIKES AND COMMENTS PER DAY Thursday, 25 April 13

21. #BDW13 3.2 BILLION LIKES AND COMMENTS PER DAY OVER HALF A PETABYTE … EVERY 24 HOURS Thursday, 25 April 13

22. #BDW13 #HADRON Thursday, 25 April 13

23. 150 MILLION SENSORS DELIVERING DATA 40 MILLION TIMES PER SECOND #BDW13 #HADRON Thursday, 25 April 13

24. 150 MILLION SENSORS DELIVERING DATA 40 MILLION TIMES PER SECOND 10’s OF PETABYTES PER YEAR #BDW13 #HADRON Thursday, 25 April 13

25. A TYPICAL COMPANY Thursday, 25 April 13

26. A TYPICAL COMPANY 100 EMPLOYEES Thursday, 25 April 13

27. A TYPICAL COMPANY 100 EMPLOYEES 10,000 CUSTOMERS Thursday, 25 April 13

28. A TYPICAL COMPANY 100 EMPLOYEES 10,000 CUSTOMERS 25 DATABASES (customers, transactions, etc) Thursday, 25 April 13

29. A TYPICAL COMPANY 100 EMPLOYEES 10,000 CUSTOMERS 1 MILLION TRANSACTIONS RECORDS 25 DATABASES (customers, transactions, etc) Thursday, 25 April 13

30. A TYPICAL COMPANY 100 EMPLOYEES 10,000 CUSTOMERS 1 MILLION TRANSACTIONS RECORDS 5,000 BYTES PER TRANSACTION 25 DATABASES (customers, transactions, etc) Thursday, 25 April 13

31. A TYPICAL COMPANY 100 EMPLOYEES 10,000 CUSTOMERS 1 MILLION TRANSACTIONS RECORDS 5,000 BYTES PER TRANSACTION 25 DATABASES (customers, transactions, etc) =4 GIGABYTES (for largest database) Thursday, 25 April 13

32. A TYPICAL COMPANY 100 EMPLOYEES 10,000 CUSTOMERS 1 MILLION TRANSACTIONS RECORDS 5,000 BYTES PER TRANSACTION 25 DATABASES (customers, transactions, etc) =4 GIGABYTES (for largest database) =20 GIGABYTES (for ALL company data) Thursday, 25 April 13

33. A TYPICAL HARDDRIVE 2000 GIGABYTES (2TB) Thursday, 25 April 13

34. A TYPICAL HARDDRIVE 2000 GIGABYTES (2TB) 4000 GIGABYTES (4TB) Thursday, 25 April 13

35. 3. YOU NEED *LOTS* OF DATA SCIENTISTS #DILBERT#BDW13 Thursday, 25 April 13

36. 3. YOU NEED *LOTS* OF DATA SCIENTISTS #DILBERT#BDW13 Thursday, 25 April 13

37. 4. HOW BIG DATA IS USED #BDW13 Thursday, 25 April 13

38. 4. HOW BIG DATA IS USED #BDW13 BANKING Thursday, 25 April 13

39. 4. HOW BIG DATA IS USED #BDW13 BANKING COMMUNICATIONS Thursday, 25 April 13

40. 4. HOW BIG DATA IS USED #BDW13 BANKING COMMUNICATIONS GOVERNMENT Thursday, 25 April 13

41. 4. HOW BIG DATA IS USED #BDW13 Thursday, 25 April 13

42. 4. HOW BIG DATA IS USED #BDW13 WEB LOGS 51% Thursday, 25 April 13

43. 4. HOW BIG DATA IS USED #BDW13 WEB LOGS 51% CLICK STREAM 35% Thursday, 25 April 13

44. 5. HADOOP GONE BAD + SQL #BDW13 #HADOOPGONEBAD Thursday, 25 April 13

45. RDBM - RELATIONAL DATABASE #BDW13 Thursday, 25 April 13

46. RDBM - RELATIONAL DATABASE NEEDS TO BE PRE-DEFINED #BDW13 Thursday, 25 April 13

47. RDBM - RELATIONAL DATABASE NEEDS TO BE PRE-DEFINED REQUIRES INDEX TO PERFORM #BDW13 Thursday, 25 April 13

48. RDBM - RELATIONAL DATABASE NEEDS TO BE PRE-DEFINED REQUIRES INDEX TO PERFORM QUERIES ARE CONSTRAINED #BDW13 Thursday, 25 April 13

49. MAP REDUCE #MAPREDUCE#BDW13 Thursday, 25 April 13

50. MAP REDUCE PROCESS CLOSE TO THE DATA #MAPREDUCE#BDW13 Thursday, 25 April 13

51. MAP REDUCE PROCESS CLOSE TO THE DATA PARALLEL EXECUTION #MAPREDUCE#BDW13 Thursday, 25 April 13

52. MAP REDUCE PROCESS CLOSE TO THE DATA PARALLEL EXECUTION ANY TYPE OF ANALYSIS #MAPREDUCE#BDW13 Thursday, 25 April 13

53. MAP REDUCE PROCESS CLOSE TO THE DATA PARALLEL EXECUTION ANY TYPE OF ANALYSIS HIDES DETAILS OFFAULT TOLERANCE, LOCALITY AND LOAD BALANCING #MAPREDUCE#BDW13 Thursday, 25 April 13

54. BIG DATA SCHEMA #NOSQL HBASE COLUMNS FILES #BDW13 Thursday, 25 April 13

55. (QUICK ASIDE) #SIDEBARThursday, 25 April 13

56. GOOGLE FILE SYSTEM (GFS) GOOGLE MAPREDUCE (GMR). GOOGLE STARTED ALL THIS.... Thursday, 25 April 13

57. GOOGLE DREMEL http://bit.ly/mS8QxX#BDW13 Thursday, 25 April 13

58. GOOGLE DREMEL INTERACTIVE ANALYSIS http://bit.ly/mS8QxX#BDW13 Thursday, 25 April 13

59. GOOGLE DREMEL INTERACTIVE ANALYSIS SCALE UP TO 10,000 SERVERS http://bit.ly/mS8QxX#BDW13 Thursday, 25 April 13

60. GOOGLE DREMEL INTERACTIVE ANALYSIS SCALE UP TO 10,000 SERVERS COLUMN STORAGE http://bit.ly/mS8QxX#BDW13 Thursday, 25 April 13

61. OpenDremel GOOGLE BIG QUERY Google Big Query #BDW13 Thursday, 25 April 13

62. http://research.google.com/archive/spanner.html GOOGLE SPANNER #SPANNER #NEWSQL Thursday, 25 April 13

63. http://research.google.com/archive/spanner.html GOOGLE SPANNER #SPANNER #NEWSQL Thursday, 25 April 13

64. http://research.google.com/archive/spanner.html GOOGLE SPANNER #SPANNER #NEWSQL RELATIONAL DATABASE Thursday, 25 April 13

65. http://research.google.com/archive/spanner.html GOOGLE SPANNER #SPANNER #NEWSQL RELATIONAL DATABASE GLOBALLY DISTRIBUTED Thursday, 25 April 13

66. http://research.google.com/archive/spanner.html GOOGLE SPANNER #SPANNER #NEWSQL RELATIONAL DATABASE GLOBALLY DISTRIBUTED USE GPS / TRUETIME Thursday, 25 April 13

67. http://research.google.com/archive/spanner.html GOOGLE SPANNER #SPANNER #NEWSQL RELATIONAL DATABASE GLOBALLY DISTRIBUTED USE GPS / TRUETIME NO OPEN SOURCE EQUIVALENT Thursday, 25 April 13

68. Thursday, 25 April 13

69. BIG DATA IS THE NEW OIL Thursday, 25 April 13

70. NICK HALSTEAD, FOUNDER HTTP://DATASIFT.COM WE ARE HIRING!! Thursday, 25 April 13

Big Data Week - Myths and Legends

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Big Data Week - Myths and Legends