1. Okay, we have a

2. Now what?

3. Suppose I need these two values Every week on new data

4. Don’t paste!

5. Make repeatable analyses (without clicking) Easily add data

6. Structured query language

7. Developed at IBM

8. Structured query language Developed at IBM Usually NOT considered a programming language

9. Structured query language Developed at IBM Usually NOT considered a programming language But a “domain specific language”

10. Structured query language Developed at IBM Usually NOT considered a programming language But a “domain specific language” Aimed at analyzing and manipulating DATA

19. Suppose I need these two values Every week on new data

21. Where is like ‘filter’ in Excel

23. But we need temperature?

24. In Excel, we did a lookup

27. Temperature is here

28. To fix a bit (move rows up)

31. This results in Carthesian product

36. This is called a ‘JOIN’

39. Very similar to VLOOKUP

42. We have a temperature field now

45. We have the filter

46. We still need to show: Machine & temperature

50. Benefit over Excel: We can have multiple such queries

51. Benefit over Excel: We can have multiple such queries

53. We have the right data

54. We have the right data But! We need ‘pivot like’ summary on average

58. AVG of what? Of everything? Per machine?

59. AVG of what? Of everything? Per machine?

65. Almost there!

67. Suppose I need these two values Every week on new data

74. Remember lecture 1?

79. Make repeatable analyses (without clicking) Easily add data

82. Can’t pick field names now

85. We made an easily repeatable analysis!