Architectures Real-time business intelligence

1 architectures

1.1 event-based
1.2 data warehouse
1.3 server-less technology
1.4 process-aware
1.5 technologies support real-time analytics

architectures

event-based

real-time business intelligence systems event driven, , may use complex event processing, event stream processing , mashup (web application hybrid) techniques enable events analysed without being first transformed , stored in database. these in-memory database techniques have advantage high rates of events can monitored, , since data not have written databases data latency can reduced milliseconds.

data warehouse

an alternative approach event driven architectures increase refresh cycle of existing data warehouse update data more frequently. these real-time data warehouse systems can achieve near real-time update of data, data latency typically in range minutes hours. analysis of data still manual, total latency different event driven architectural approaches.

server-less technology

the latest alternative innovation real-time event driven and/or real-time data warehouse architectures msso technology (multiple source simple output) removes need data warehouse , intermediary servers altogether since able access live data directly source (even multiple, disparate sources). because live data accessed directly server-less means, provides potential zero-latency, real-time data in truest sense.

process-aware

this considered subset of operational intelligence , identified business activity monitoring. allows entire processes (transactions, steps) monitored, metrics (latency, completion/failed ratios, etc.) viewed, compared warehoused historic data, , trended in real-time. advanced implementations allow threshold detection, alerting , providing feedback process execution systems themselves, thereby closing loop .

technologies support real-time analytics

technologies can supported enable real-time business intelligence data visualization, data federation, enterprise information integration, enterprise application integration , service oriented architecture. complex event processing tools can used analyze data streams in real time , either trigger automated actions or alert workers patterns , trends.

data warehouse appliance
data warehouse appliance combination of hardware , software product designed exclusively analytical processing. in data warehouse implementation, tasks involve tuning, adding or editing structure around data, data migration other databases, reconciliation of data done dba. task dba make database perform large sets of users. whereas data warehouse appliances, vendor responsibility of physical design , tuning software per hardware requirements. data warehouse appliance package comes own operating system, storage, dbms, software, , required hardware. if required data warehouse appliances can integrated other tools.


mobile technology
there limited vendors providing mobile business intelligence; mbi integrated existing bi architecture. mbi package uses existing bi applications people can use on mobile phone , make informed decision in real time.