Reduce Development Time And Effort With Metadata-Generated BI Applications
Complexity represents one of the toughest challenges facing traditional business intelligence (BI) applications. Multiple components must be considered including data integration, cleansing, modeling, warehousing, metrics creation and management, reports, dashboards, queries, alerts, and many more, with infinite approaches to cobble them together into a useful and meaningful BI application. This multitude of components and complexities makes rapid prototyping challenging at best, impossible at worst. Furthermore, there typically isn’t such an option as a “quick change” for a BI application, since so many tightly coupled components are usually affected. To address this challenge, Forrester sees an emergence of a new generation of metadata-generated BI applications that BI professionals should consider — not as a replacement for traditional BI, not yet — but for specific use cases such as complementing traditional BI, generating data marts from the enterprise data warehouse (EDW), and delivering rapid BI application prototypes.
Why traditional bi applications are not agile by design
The information-based economy is here, and enterprises reap many benefits. Businesses and governments get more information about their internal and externally facing processes, customers, and products. Strategic and operational decision-makers make better-informed decisions based on advanced and often faster insight than their competitors. But numerous information era advances and benefits can come with a cost, often causing knowledge workers to drown in mountains of data. Traditional BI applications were invented in the 1980s to address precisely this problem: helping these knowledge workers sift through high volumes of data and transform it into meaningful, useful, and insightful information.
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