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Introduction to Business Intelligence
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report authors to circumvent these constraints With BusinessObjects, report authors can query multiple subject areas and stitch the results together seamlessly, locally Synchronized multiple data providers is probably the single most anticipated feature in Web Intelligence XI Release 2 With a data warehouse, the data is combined into one subject area or business view, allowing users to perform analyses that cut across multiple business processes This approach puts significantly less strain on the BI application and is more scalable than attempting to put so much logic within one report As the data is aggregated, data warehouses can contain years of history, allowing users to analyze trends; ERP and transaction systems often contain only current data at the most granular level of detail preventing any kind of trend analysis Table 1-1 compares some of the different purposes and features of a transaction system with those of a data warehouse
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PART I PART I PART I
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The Internet Influence
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With the Internet boom of the late 1990s, the Web has had a dramatic impact on BI A large deployment in a client/server deployment may have been in the thousands; in a Web deployment, it s tens of thousands What once was viewed as a departmental application is now considered an enterprise resource In some cases, the corporate intranet is no longer the deployment boundary, as customers and suppliers can also access rich BI content from a browser
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ERP/Transaction System Goal is to process orders, post journal entries Current information with very little history Data Warehouse / Data Mart Goal is to provide access to information to improve revenues, manage costs, improve customer service, achieve strategic goals Larger amounts of history allow multiyear trend analysis, this year versus last year comparisons Information extracted on a periodic basis (hourly, daily, weekly, and so on) Aggregated data but increasingly granular Read-only; tuned for fast queries Denormalized star or snowflake schemas with fewer tables Hierarchical groups give level of time, chart of accounts, product groupings, customer groups, and so on Fixed or ad hoc reporting and analysis by multiple dimensions across all business functions
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Real-time information Detailed data down to the line item or level of data entry Fast inputs, but slow queries Normalized tables in thousands Rarely hierarchical groupings
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Fixed reports by one detailed dimension (cost center, plant, order number)
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TABLE 1-1 Comparison of Transaction Systems with Data Warehouses
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Part I:
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Getting Ready for BusinessObjects XI
To leverage the Web, many BI vendors have re-architected their products The industry still hotly debates Web delivery and authoring approaches A browser interface is not always as intuitive as a Windows environment and lacks the maturity and consistent design of Windows-based applications For this reason, Business Objects is continuing to provide a desktop authoring tool, Crystal Reports, for high-fidelity production-style reports, developed by professional report authors Web Intelligence, meanwhile, is a purely Webbased authoring tool, ideally for business users who may not need all the advanced design tools that an IT developer requires Yet to provide a certain amount of intuitiveness, Web Intelligence has two interfaces: an applet that has a richer design experience and a zerofootprint HTML version that is more wizard-like for basic reports Desktop Intelligence, formerly called BusinessObjects classic, allows long-time customers to preserve their report development investments while offering a migration strategy The user interface is only one aspect of a Web-based BI deployment that the industry and customers alike need to rethink The other is clearly the architecture BusinessObjects XI Release 1 (released December 2004) certainly was about integrating the Crystal and BusinessObjects product lines, but it was also about providing a scalable architecture for Web-based BI As deployments grow increasingly larger, with 24 by 7 access, and no downtime, the architecture must be more fault-tolerant and use shared services (discussed more in 5)
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