[{"data":1,"prerenderedAt":277},["ShallowReactive",2],{"navigation":3,"page-\u002Fen\u002Ffoundations\u002Farchitecture-and-data-flow":88,"\u002Fen\u002Ffoundations\u002Farchitecture-and-data-flow-surround":271,"comments-\u002Fen\u002Ffoundations\u002Farchitecture-and-data-flow":276},[4],{"title":5,"path":6,"stem":7,"children":8,"page":87},"En","\u002Fen","en",[9,53],{"title":10,"path":11,"stem":12,"children":13,"icon":52},"CRM Analytics Foundations","\u002Fen\u002Ffoundations","en\u002F1.foundations\u002F1.index",[14,16,20,24,28,32,36,40,44,48],{"title":15,"path":11,"stem":12},"Welcome & Dev Org",{"title":17,"path":18,"stem":19},"Graded Quiz","\u002Fen\u002Ffoundations\u002Fquiz","en\u002F1.foundations\u002F10.quiz",{"title":21,"path":22,"stem":23},"What Is CRM Analytics?","\u002Fen\u002Ffoundations\u002Fwhat-is-crm-analytics","en\u002F1.foundations\u002F2.what-is-crm-analytics",{"title":25,"path":26,"stem":27},"Architecture","\u002Fen\u002Ffoundations\u002Farchitecture-and-data-flow","en\u002F1.foundations\u002F3.architecture-and-data-flow",{"title":29,"path":30,"stem":31},"The Data Layer","\u002Fen\u002Ffoundations\u002Fthe-data-layer","en\u002F1.foundations\u002F4.the-data-layer",{"title":33,"path":34,"stem":35},"The Design Layer","\u002Fen\u002Ffoundations\u002Fthe-design-layer","en\u002F1.foundations\u002F5.the-design-layer",{"title":37,"path":38,"stem":39},"The Intelligence Layer","\u002Fen\u002Ffoundations\u002Fthe-intelligence-layer","en\u002F1.foundations\u002F6.the-intelligence-layer",{"title":41,"path":42,"stem":43},"Hands-On Tour","\u002Fen\u002Ffoundations\u002Fhands-on-tour","en\u002F1.foundations\u002F7.hands-on-tour",{"title":45,"path":46,"stem":47},"Six Adoption Steps","\u002Fen\u002Ffoundations\u002Fsix-steps-and-interview-prep","en\u002F1.foundations\u002F8.six-steps-and-interview-prep",{"title":49,"path":50,"stem":51},"Interview Questions","\u002Fen\u002Ffoundations\u002Finterview-questions","en\u002F1.foundations\u002F9.interview-questions","i-lucide-compass",{"title":54,"path":55,"stem":56,"children":57,"icon":86},"Setup & User Provisioning","\u002Fen\u002Fsetup","en\u002F2.setup\u002F1.index",[58,60,64,68,72,76,80,83],{"title":59,"path":55,"stem":56},"Provisioning Users",{"title":61,"path":62,"stem":63},"Licenses & Permissions","\u002Fen\u002Fsetup\u002Flicenses-and-permission-sets","en\u002F2.setup\u002F2.licenses-and-permission-sets",{"title":65,"path":66,"stem":67},"Integration User","\u002Fen\u002Fsetup\u002Fthe-integration-user","en\u002F2.setup\u002F3.the-integration-user",{"title":69,"path":70,"stem":71},"Security User","\u002Fen\u002Fsetup\u002Fthe-security-user","en\u002F2.setup\u002F4.the-security-user",{"title":73,"path":74,"stem":75},"Analytics Settings","\u002Fen\u002Fsetup\u002Fanalytics-settings","en\u002F2.setup\u002F5.analytics-settings",{"title":77,"path":78,"stem":79},"Hands-On Access","\u002Fen\u002Fsetup\u002Fhands-on-assigning-access","en\u002F2.setup\u002F6.hands-on-assigning-access",{"title":17,"path":81,"stem":82},"\u002Fen\u002Fsetup\u002Fquiz","en\u002F2.setup\u002F7.quiz",{"title":49,"path":84,"stem":85},"\u002Fen\u002Fsetup\u002Finterview-questions","en\u002F2.setup\u002F8.interview-questions","i-lucide-settings-2",false,{"id":89,"title":90,"access":91,"body":92,"description":261,"extension":262,"interview":91,"links":91,"meta":263,"navigation":264,"passScore":91,"path":26,"quiz":91,"seo":265,"stem":27,"video":266,"__hash__":270},"docs\u002Fen\u002F1.foundations\u002F3.architecture-and-data-flow.md","How CRM Analytics Fits: Architecture & Data Flow",null,{"type":93,"value":94,"toc":250},"minimark",[95,99,112,117,120,125,129,137,157,160,164,167,185,188,192,214,218,225,232,236,239,243],[96,97,90],"h1",{"id":98},"how-crm-analytics-fits-architecture-data-flow",[100,101,102,103,107,108,111],"p",{},"Now that you know ",[104,105,106],"em",{},"what"," CRM Analytics is, let's look at ",[104,109,110],{},"how"," it fits together. You do not need to memorize an engineering diagram, but a simple mental map of the architecture and data flow will make every later lesson — data sync, recipes, live connections — click into place. The clip above walks through this at a high level; here is the same picture in words.",[113,114,116],"h2",{"id":115},"getting-data-in","Getting data in",[100,118,119],{},"CRM Analytics is only as useful as the data you feed it, so it offers several on-ramps:",[121,122],"lesson-cards",{":columns":123,":items":124},"3","[{\"title\":\"Native Salesforce connector\",\"icon\":\"i-lucide-cloud\",\"description\":\"Pull standard and custom objects with no middleware, drivers, or exports — point it at Accounts, Opportunities, Cases, and it just works.\"},{\"title\":\"Other-cloud connectors\",\"icon\":\"i-lucide-plug\",\"description\":\"Prebuilt connectors reach external systems — other orgs, marketing clouds, data warehouses — to bring their data alongside CRM data.\"},{\"title\":\"CSV upload\",\"icon\":\"i-lucide-file-spreadsheet\",\"description\":\"Upload a spreadsheet directly for one-off or reference data.\"},{\"title\":\"ETL \u002F API ingestion\",\"icon\":\"i-lucide-workflow\",\"description\":\"For industrial needs, an external ETL tool or the analytics API can push data in on a schedule.\"}]",[113,126,128],{"id":127},"where-the-data-lands-datasets","Where the data lands: datasets",[100,130,131,132,136],{},"However data arrives, it ultimately lands in ",[133,134,135],"strong",{},"datasets",". A dataset is CRM Analytics' optimized, columnar storage format, engineered for fast queries over large volumes. Once you have datasets in place, the real fun begins:",[138,139,140,151],"ul",{},[141,142,143,146,147,150],"li",{},[133,144,145],{},"Combine datasets"," — join or blend multiple sources so a single analysis can span, say, opportunities ",[104,148,149],{},"and"," external revenue data.",[141,152,153,156],{},[133,154,155],{},"Create derived fields"," — compute new values (ratios, buckets, flags) that did not exist in the source.",[100,158,159],{},"This is where raw data becomes a shaped, analysis-ready model.",[113,161,163],{"id":162},"live-vs-replicated-data","Live vs. replicated data",[100,165,166],{},"Not every source needs to be copied. CRM Analytics supports two philosophies:",[168,169,171],"note",{"icon":170},"i-lucide-git-compare",[100,172,173,176,177,180,181,184],{},[133,174,175],{},"Replicated data"," is copied into a dataset — fast to query, but a point-in-time snapshot. ",[133,178,179],{},"Live connections (Direct Data)"," query the source system in real time — for example, running against ",[133,182,183],{},"Snowflake"," directly so you always see current data without duplicating it.",[100,186,187],{},"Replication gives you blistering speed and the ability to blend and transform freely. Live\u002FDirect Data gives you freshness and avoids storing another copy. Real-world architectures often use both, choosing per source based on volume, freshness needs, and governance.",[113,189,191],{"id":190},"getting-data-back-out","Getting data back out",[100,193,194,195,198,199,202,203,206,207,209,210,213],{},"The flow is ",[133,196,197],{},"bidirectional",". CRM Analytics is not a dead end where data goes to be viewed and forgotten. Through ",[133,200,201],{},"output connections",", it can push results back out to other systems — for example to ",[133,204,205],{},"AWS S3",", ",[133,208,183],{},", or ",[133,211,212],{},"Tableau Hyper"," extracts. That means the shaped, enriched, or scored data you build here can feed downstream warehouses, other BI tools, or data lakes.",[113,215,217],{"id":216},"dedicated-virtualized-compute","Dedicated, virtualized compute",[100,219,220,221,224],{},"Here is the architectural detail that ties it all together, and it echoes the previous lesson. CRM Analytics runs on ",[133,222,223],{},"dedicated, virtualized compute"," — separate from the transactional database that powers your live Salesforce app.",[100,226,227,228,231],{},"Why does this matter? Analytics is ",[104,229,230],{},"heavy",". Scanning millions of rows, joining datasets, and training models would grind an operational database to a halt and hurt every user trying to save a record. By running analytics on its own compute layer against optimized datasets, CRM Analytics keeps your day-to-day CRM snappy while still crunching serious volume behind the scenes.",[113,233,235],{"id":234},"the-big-picture","The big picture",[100,237,238],{},"Put it together and the flow reads left to right, then back:",[240,241],"lesson-steps",{":items":242},"[{\"title\":\"Ingest\",\"description\":\"Bring data in via the native connector, other-cloud connectors, CSV upload, ETL\u002FAPI, or a live connection.\"},{\"title\":\"Land in a dataset\",\"description\":\"Data settles into optimized, columnar datasets built for fast queries at scale.\"},{\"title\":\"Combine & derive\",\"description\":\"Join or blend datasets and create derived fields to shape an analysis-ready model.\"},{\"title\":\"Build & output\",\"description\":\"Explore in lenses and dashboards on dedicated compute, and push results back out to S3, Snowflake, or Tableau Hyper.\"}]",[100,244,245,246,249],{},"Keep this map in mind. In the next lesson we zoom into the ",[133,247,248],{},"data layer"," itself — sync, recipes, dataflows, and the datasets that make all of this fast.",{"title":251,"searchDepth":252,"depth":253,"links":254},"",1,2,[255,256,257,258,259,260],{"id":115,"depth":253,"text":116},{"id":127,"depth":253,"text":128},{"id":162,"depth":253,"text":163},{"id":190,"depth":253,"text":191},{"id":216,"depth":253,"text":217},{"id":234,"depth":253,"text":235},"A simple map of CRM Analytics architecture: connectors, CSV upload, ETL\u002FAPI ingestion, datasets, live connections, output, and dedicated compute in Salesforce.","md",{},{"title":25},{"title":90,"description":261},{"id":267,"start":268,"end":269},"aPwndqsmaGk",515,662,"WliHLEgQjhNfQvMaD-ovQtgaKeztEDwKutsUKAjoDk4",[272,274],{"title":21,"path":22,"stem":23,"description":273,"children":-1},"Understand what CRM Analytics (Tableau CRM) is: Salesforce's intelligent analytics platform that adds predictions and augmented insight on top of your CRM data.",{"title":29,"path":30,"stem":31,"description":275,"children":-1},"Inside the CRM Analytics data layer: Data Sync staging, Dataflow vs. Data Prep recipes, and the optimized datasets that make queries fast at high volume.",[],1783454189194]