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Extra resources for Advances in Computers, Vol. 13

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MWorld, J Am Manage Assoc, Winter 2012À2013. 38 Business Intelligence Strategy and Big Data Analytics More broadly, we previously defined BI as an umbrella term that encompasses provision of relevant reports, scorecards, dashboards, email alerts, prestructured user-specified queries, ad hoc query capabilities, multidimensional analyses, statistical analyses, forecasts, models, and/or simulations to business users for use in increasing revenues, reducing costs, or both. Typical business intelligence (BI) applications—all of which leverage business data and provide analytical perspectives— include: • REPORTS: standard, preformatted information for backwardlooking analysis of business trends, events, and performance results; • MULTIDIMENSIONAL ANALYSES: applications that leverage a common database of trusted business information and that fully automate information slicing and dicing for analysis of the underlying drivers of business events, trends, and performance results; • SCORECARDS and DASHBOARDS: convenient forms of multidimensional analyses that are common across an organization, that enable rapid evaluation of business trends, events, and performance results, and that facilitate use of a common management framework and vocabulary for measuring, monitoring, and improving business performance; • ADVANCED ANALYTICS: automated applications that distill historical business information so that past business trends, events, and results can be summarized and analyzed via well-known and long-used statistical methods; • PREDICTIVE ANALYTICS: automated applications that leverage historical business information, descriptive statistics, and/or stated business assumptions to predict or simulate future business outcomes that can be analyzed for their business impact; and • ALERTS: automated process control applications that analyze performance variables, compare results to a standard, and report variances outside defined performance thresholds.

Trade Promotion Analytics. This BIO would integrate trade spending, IRI, and ERP data as needed to automate promotion level analysis and deliver promotion performance metrics. Having ready access to such information will benefit BBF during market and brand planning processes and during the process of targeting trade support toward programs and customers The Personal Face of Business Intelligence 4. 5. 6. 7. 19 whose performance has been proven. There is a huge opportunity to more effectively allocate the $900 million in trade support investments by leveraging BI to automate the postpromotion analysis process and view promotions by customer and type.

2. Difference—traditional BI tools are used to analyze structured data, whereas cognitive business applications would have both structured and unstructured data as inputs. Given the need to analyze unstructured data, there are a variety of tools that are used to basically take unstructured data and describe it in ways so that it can be processed by computerized algorithms. From a business perspective, what might be important is if your particular company needs to move beyond more traditional BI and analytics to analyze large amounts of unstructured data in order to improve some relevant business process in a way that increases revenues, reduces costs, or both.

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