Architecture Modernization with Cloudera
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[pic 1][pic 2][pic 3][pic 4][pic 5][pic 6]Architecture modernizationDear AttendeesArchitecture modernization Who doesn’t want want to work with the latest architecture ?But who knows what this is ?After our presentation you will know better why you should modernize your architecture, are you more aware of differetent tools available and .. and will you get a better insight in things to do
Big data analytics works in a different way.  All data is captured in case it’s needed, multistructured. Business explores the data to find questions worth answeringWho will be our customers in 6 months and where will they come from?In this world new analytics is used likePath analysis (eg to see how customers move from gold to silver to bronze customer card over time Text analytics; finding out how people react on your commercials via reading tweetsGraph Analytics eg find which customer is most influential and should be rewardedMap reduceFast Data AnalyticsMore and more we want to act on real time/ near real time events. First we need to do the analysis in the given time frame, next we have to react.Examples of this are Event DetectionFraud/Risk DetectionSpam FilterMarketing AlertsRecommendation EngineNext Best OfferContent and/or Services RecommendationModel scoringEmbedded AnalyticsAnalytic AggregatesReportsTRANSITION: Now we have seen the changes in Data usage it is time to switch to architectural viewsArchitecture ViewLets go to the architecture viewSchema on read is the change agentAn important aspect of the enterprise data hub is support for both schema on write and schema on read in order to handle routine and exploratory workloads.Schema on write (as with traditional databases) provides good performance as it is possible to lay out the data efficiently, as well as good governance.Schema on read allows users to store any data as the system looks more like a file system than a database. It effectively performs ETL (extract, transform, load) on the fly at read time, generating the appropriate schema as part of the process. This means an additional column of data can be provided for analysis very quickly.The logical architecture hasn’t changedWe see here the logical architecture of Datawarehousing . Ralph Kimball talked about it in the seminar The Future of data ware housing. ETL will never be the same. I don’t want to go into the details of this architecture but highlight the fundamental differences. Ralph talks about the EDW backroom and the EDW frontroomWe see data coming in from the orginal source systems, being processed  in the ETL step  , Data exposed into the the presentation layer and  the BI applications BUT, the physical architecture of the back room now looks very differentWhen we bring our Enterprise Data Hub into the game we bring in HDFS files and most imprortant Schema on readOld Backroom