Principles :$QUEST$
• Ques)on$
– be$very$clear$on$what$the$ques)ons$you$are$trying$to$answer$
• ques)ons$can$change$mid$way,$but$all$things$you$do$is$toward$answering$ques)ons$$
• part$of$the$work$may$be$towards$figuring$out$what$ques)ons$to$ask$to$data,$then$the$ques)on$is$“what$can$I$learn$from$
the$data$that’s$useful$to$my$business”$
– if$you$are$not$answering$a$ques)on,$you$may$be$at$a$different$stage,$such$as$data$engineering$
• Unknowns$N$know$what$you$do$not$know$
– be$very$clear$on$what’s$unknown$and$the$assump)ons$made$explicitly$or$implicitly$made$
• assume$there$are$unknowns,$check$for$$
• know$the$assump)ons$that$comes$with$the$formula$
• Explore$
– looking$at$the$data$from$different$perspec)ves,$drill$down$and$up,$zooming$in$to$different$part$of$the$data,$$
– look$for$external$data$to$enrich$and$validate$your$data$
• Scrupulous$vs.$Speed,$Science$vs.$Scrappiness$
– painstakingly$check$you$scripts/methods$while$knowing$that$speed$to$insight$and$produc)on$is$cri)cal$
– hold$highest$scien)fic$standard,$but$willing$to$go$scrappy$when$needed$while$being$inten)onal$
• Truth$
– truth$about$the$world$that$my$business$is$operate$in$
– truth$about$the$data$itself$will$help$but$cannot$directly$generalize$to$truth$about$the$world$