2. 3. Data Data are values of qualitative orquantitative
variables, belong to aset of items.Set of items : Sometimes called
the population; the set of objects you are interested in.Variables
: A measurement or characteristic of an itemQualitative : Country
of origin, sex, treatment...Quantitative : Height, weight, blood
pressure... 4. Set of ItemOxford : (fact, raw material) , , 5.
(qualitative data) (quantitative data) . : , : , , , 6. . , . 7.
The data is the second most important thing The most important
thing in data science is the question The second most important is
data Often the data will limit or enable the question But having
data cant save you if you dont have a question 8. 9. , 1950 1960
1970 (-1981 ) 1980 1990 ~ (SQL) 2010 big data NoSql 10. ACID
(Atomicity) : . All or Nothing" . (Consistency) : . (Isolation) : .
(Durability) : () . 11. Big Data (INPUT)? (OUTPUT)? 12. CAP 2000
(Eric Brewer) , CAP(CAP Theorem), (Brewers theorem) . , ,
(Consistency) = . (Availability) = . (Partition Tolerance) = . 13.
CAP CP ( + = )AP ( + = ) 14. NoSqlNot-Only-SQL Key-Value : .
Dynamo, Redis Ordered KeyValue : . BerkeleyDB Big Table : : Hbase
Documnet : NoSql XML,JSON : MongoDB, Cloudant 15. r !!! 16. 17.
Data 18. Big Data (Volume) (Velocity) (Variety)
VolumeVelocityVariety3V Value 19. Big Data ? 20. 21. Big Data ( )
() () (Aviva) 22. Ice Break Big Data ? Twitter 23. Hype Cycle1995 .
, .1 Technology Trigger - 2 Peak of Inflated Expectation - 3 Trough
of Disillusionment) - 4 Slope of Enlightenment - 5 Plateau of
Productivity - 24. Big Data 25. 26. 27. 28. ? 29. ? 30. ? .
Parameters 31. : : : ,
