1- Data discovery does not mean you dont have a business Problem.-What are you trying to discover?- Identify document business issueo Pharmaceuticals Advertising spend, Rx saleso Retail Market basket, sales performance.o Healthcare Hospital proftabilit, labor productivit.o !inancial services Asset management, "redit risk- You need a problem domain- no one gets paid to meandero #efne deliverables for iterative ccles $%.g. dimensions and measures, data sources to include&o Re'uired for enterprise (ustifcation- a!ea"ay o Have clear intentions of )hat information ou )ant from our program )hen ou start. *se to drive R+, and validate ac'uisition.- Prioriti#e functional area "ith strong business impact and championo - .likvie) allo)s for 'uick modeling of business issueso - %ngage in )orkshopo - #ocument metricso - /uild business case 0 R+,o - 1ou )ill see rapid R+, $)eeks vs. months&$-%ust because getting data into &li!vie" is easy does not mean you shouldnt have data architecture.- Dirty data or data that doesnt integrate "ill hold up your pro'ect 1(() of the time.o Mismatched data b time, account, descriptiono %xample2 34, market share, product level- *arbage in + garbage outo .likvie) is reall great for presenting data to users, including dirt data.o #irt data needs to be cleaned up before it delivers value.- Data is constantly changingo 5lo)l changing dimensionso #ead accounts, changed data, eliminations, etc.- a!ea"ay o .likvie) does not solve longstanding issues of data architecture. Production concepts are re'uired for enterprise $%64, M#M, Metadata, etc.&.- Data ,rchitecture- Incremental data loadso *sed in con(unction )ith a staged architecture.o Processing gains at the level of the .7# generator.o ,ncremental ro)s identifed via timestamp.o !inal .7# is a combination of ne)l extracted ro)s and prior data run.- a!ea"ay- o .likvie) lends itself to data management strategies like incremental data loading. 6his feature eases the deploment ofnumerous applications..- &li!vie" has its o"n speci/c needs in terms of enterprise architecture.- 0ven ne" technology approach re1uires ne" "ays of thin!ing.- In memoryo #edicated vs. virtual 0 shared memoro Ho) much memor do , need, cheap but not free.o Reall need to understand environment business and technolog.- Data scalability re1uires architecture design.o .7#8s, /inar loads, loop and reduce, Publisher.o #irect #iscover.- 2e" terms 3 de/nitions.o "lustering means di9erent things to di9erent peopleo %9ective for spreading apps, not true :4oad /alancing;- a!ea"ay o .likvie), like an ne) technolog, has an architectural learningcurve. 6he architecture depends on the business and technolog environment.4- Iterative development does not mean you dont need to productionali#e- 5usiness discovery enables rapid prototypingo Pull in lots of data sourceso .uickl build dashboards and vie)s.o At some point, need to make the application )orth of presentation.- 6ully understand user capabilities and re1uirement.o /usiness discover $