16. where time 21:00-22:00
count(*)
21:00 all→1345 :00→45 :01→62 :02→87 ...
where time 22:00-23:00, 22:00 all→3222 :00→22 :01→19 :02→105 ...
group by minute ... ...
UK all→229 user01→2 user14→12 user99→7 ...
where geography=UK US all→354 user01→4 user04→8 user56→17 ...
group all by user, ...
UK, 22:00 all→1905 ...
count all ∅ all→87315 UK→239 US→354 ...
group all by geo
16
Analytics
18. • Motivation / alternatives
• What is it?
• How does it work?
• Whats it good for?
18
Analytics
19. Manufacturing Social Media Ad Analytics
Systems Financial
Oil + Gas
Monitoring Services
Analytics
20. “We keep discovering use cases
we hadn’t thought of ”
“We found out a competitor
was scraping our data”
“Up and running in about 4 hours”
Analytics