It’s the ability to deliver integrated, right-time data warehousing information to all users including front-line employees, suppliers, customers, and partners. It provides an enterprise visibility, insight and facts to make smarter decisions in all processes at all times. In most companies, this means liberating existing infrastructure by connecting it to multiple operational business processes.
What role does data integration play in pervasive BI?
It certainly simplifies and it makes it more possible to become pervasive. InetSoft's unique data mashup engine allows combinations of almost any data source into a common BI infrastructure so you can make dashboards and reports that previously had to be done manually in a spreadsheet, for instance.
In the traditional approach data environments were highly fragmented. It was very difficult to move to an enterprise-wide model. Adding the operational integration in addition to integrating data enterprise wide was considered not feasible until recently. This is where we felt it would by highly valuable to describe the new information supply chain environment and pervasive BI strategy.
The pervasive BI architecture includes transactional services, for example, OLTP, that provide enterprise bookkeeping functions. This is where we find traditional call center automation, operational CRM, enterprise resource planning, supply chain management, and legacy applications. Data integration services bridge multiple domains providing both continuous streams of information as well as flat file data acquisition.
Acquiring change data from the transactional repositories, the data integration services extract, discover, cleanse, transform, and deliver the data to multiple subscribers. Decision repositories are the enterprise data warehouses, data marts, and operational data stores. They collect the results of data integration services and provide high-speed access to data content.
What are some examples of how customers are implementing pervasive BI?
One is automated insurance claims, triage, and fraud detection. Personalized next best offer on Web sites, ATMs, and point of sales devices is another set of examples. Supply chain activity monitoring, retail out of stock monitoring on promotional items, real-time money laundering are several more.