Financial Business Intelligence: Trends, Technology, Software Selection, and ImplementationTurn storehouses of data into a strategic tool Business intelligence has recently become a word used by almost every CFO, controller, and analyst. After having spent the last decade implementing Enterprise Resource Planning software and other mission critical solutions, companies now have large databases with transactional data sitting in their computer rooms. Now, finally, the technology has reached a point where it is possible- in almost real time-to quickly and easily analyze the financial data in the corporate databases, to be able to make more intelligent business decisions. This book will help financial managers understand the trends, technology, software selection, and implementation of financial business intelligence (financial BI) software. With a dictionary of business intelligence terms, a comprehensive list of Request for Proposal questions, and examples of popular financial business intelligence reroutes and user interfaces, this book enables managers to measure their companies' business intelligence and maximize its value. |
From inside the book
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Page 13
... down. Datawarehouses contain a wide variety of data that present a coherent picture of business conditions at a ... drill-down and querying. These OLAP cubes (often named data marts TRENDS 13.
... down. Datawarehouses contain a wide variety of data that present a coherent picture of business conditions at a ... drill-down and querying. These OLAP cubes (often named data marts TRENDS 13.
Page 14
... drill-down and querying. These OLAP cubes (often named data marts because they each contain a specific set of related data) can either be built or populated directly from the transaction source (e.g., a budgeting and reporting database ...
... drill-down and querying. These OLAP cubes (often named data marts because they each contain a specific set of related data) can either be built or populated directly from the transaction source (e.g., a budgeting and reporting database ...
Page 16
... through several phases since its inception half a century ago. Today, this has resulted in three different types of ... drill-down and customization on the fly) (see Figure 1.11) For years, the common way of retrieving and organizing ...
... through several phases since its inception half a century ago. Today, this has resulted in three different types of ... drill-down and customization on the fly) (see Figure 1.11) For years, the common way of retrieving and organizing ...
Page 17
... Drill-down, drill-around, and drill-through—so report users can get their questions answered without running additional reports • Direct spreadsheet integration—to provide a high level of formatting and user friendliness • Fully web ...
... Drill-down, drill-around, and drill-through—so report users can get their questions answered without running additional reports • Direct spreadsheet integration—to provide a high level of formatting and user friendliness • Fully web ...
Page 18
... Drill-down means that you can double-click on a row, column, or number in a report and the system automatically generates a new report/view for you that provides the underlying detail. With drill-around, you can also drill “sideways ...
... Drill-down means that you can double-click on a row, column, or number in a report and the system automatically generates a new report/view for you that provides the underlying detail. With drill-around, you can also drill “sideways ...
Contents
1 | |
Part Two BI Technology | 67 |
Part Three Software Evaluation and Selection | 107 |
Part Four Implementing a Business Intelligence System | 145 |
Appendix A Sample RFP | 199 |
Appendix B Software Candidate Evaluation and Rating Sheet | 221 |
Appendix C Sample License Agreement | 223 |
Appendix D Sample Confidentiality and Nondisclosure Agreement SalesDemo Process | 229 |
Appendix E Sample Support PlanAgreement | 233 |
Appendix F Sample Project Plan | 235 |
Appendix G Sample Consulting Agreement | 237 |
Appendix H Vendor Addresses | 241 |
Appendix I References and Further Reading | 249 |
Glossary | 251 |
Index | 279 |
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Common terms and phrases
1999–2001 ProClarity Corporation account numbers Advantage Pty Limited Agreement analysis analytical application balanced scorecard budget business intelligence client company’s Consultant cost create customers data mart data model data sources database datawarehouse datawarehousing decision defined desktop dimension tables drill-down end users enterprise Enterprise Information Portal ETL process evaluation example Feature Description Y/N/P FIGURE formation functionality hierarchy implementation information consumers informational needs interface Internet Item Feature Description Licensee Microsoft Microsoft Analysis Services MOLAP multidimensional OLAP cube OLTP online analytical processing organization performance portal ProClarity Professional Advantage Pty project plan Reply Vendor Item report writers requirements revenue ROLAP server snowflake schema software selection solution source data specific spreadsheet star schema tion today’s Toll Free transaction typically updates Vendor Item Feature Vendor Reply Vendor warehouse web-based XBRL
Popular passages
Page 266 - Management control is the process by which managers assure that resources are obtained and used effectively and efficiently in the accomplishment of the organization's objectives.
Page 270 - Query Response Times The time it takes for the warehouse engine to process a complex query across a large volume of data and return the results to the requester. Query Tools Software that allows a user to create and direct specific questions to a database. These tools provide the means for pulling the desired information from a database. They are typically SQL-based tools and allow a user to define data in end-user language.
Page 273 - Standard Cost System A system by which production activities are recorded at standard costs and variances from actual costs are isolated. Standard Costs Production or operating costs that are carefully predetermined.
Page 272 - The ability to scale to support larger or smaller volumes of data and more or fewer users. The ability to increase or decrease size or capability in cost-effective increments with minimal impact on the unit cost of business and the procurement of additional services.
Page 267 - Normalization - The process of reducing a complex data structure into its simplest, most stable structure. In general, the process entails the removal of redundant attributes, keys, and relationships from a conceptual data model.
References to this book
Marktorientierte Steuerungsgrößen mit Hilfe von Datenbanken - dargestellt an ... Dennis Grzywatz No preview available - 2008 |