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Cloud Computing: Dissecting the Components of Business Intelligence in the Cloud
To understand anything better, a good idea is to break the concept down into smaller components. And Cloud Computing is one area that a lot of people really would like to understand better. The Gartner Group has tried to do that by dissecting the meaning of Business Intelligence in the Cloud, or what Gartner calls ‘Cloud Computing Analytics‘, into six component pieces:
- Data Sources
- Data Models
- Processing applications
- Computing power
- Analytic models
- Storing results
SaaS-based Business Intelligence applications are looking attractive to a lot of marketing organizations now, but Gartner points out that these applications in themselves may not be of much value without the actual data to analyze, and that data is often currently in-house and controlled by the IT group. In order for the scenario to work where marketing uses BI in the clouds, marketing will often need to secure good cooperation from IT to get access to their data and data models. Gartner says that SaaS-based BI vendors tend to directly target sales and marketing groups, trying to get their foot in the door without having to deal with tech-savvy IT people.
It’s good to have the checklist of six components available when comparing and analyzing the various companies in the marketplace that call themselves cloud analytics vendors. There is a wide variety of vendor interpretations about what cloud analytics is and that is reflected in the range of different types of features available in their offerings. Some vendors offer “social networking analytics”, others offer more of a data warehouse analytics database.
The Gartner report summarizes the situation by saying that “Cloud analytics isn’t a single, uniform product or technology category. To gain any business advantage from it, enterprises must have a clear idea of what they mean when they use the term.”
