Organizations have implemented enterprise applications such as ERP and CRM for business process execution but have failed to address the key enterprise asset: data. In the current economic environment, enterprises that fail to capitalize on their data assets jeopardize their cost structures and their earnings potential. It is vital for organizations to leverage their data assets to measure their business performance, identify the weak poles and strategic improvement spots to scale their business to new heights. Business Intelligence (BI), the recent innovation in IT, has emerged to be a potential hope for the organizations to build a strong business milieu without any new asset investments and utilizing the existing key assets of the organizations.
Best Business Intelligence (BI) Practices to
Transform Your Data into InformationTable of Contents
Summary 3-----------------------------------------------------------------
Introduction 4 -------------------------------------------------------------
Methodologie 4 s -----------------------------------------------------------
Data Collecti o n 4 ----------------------------------------------------------Informat io n 5--------------------------------------------------------------Visio n 5 -------------------------------------------------------------------
The BI Pyramid 6----------------------------------------------------------
Organization Readiness 7-------------------------------------------------Architecture 7-------------------------------------------------------------Process 7-----------------------------------------------------------------Alignment 7---------------------------------------------------------------Key Performance Indicators (KPIs) 8--------------------------------------
Best BI Practices 8--------------------------------------------------------
Choosing Right Partner 9--------------------------------------------------
Case Study - BI for Sales Analysis & Reporting 9-----------------------
Client Background 9------------------------------------------------------Business Requirement 9--------------------------------------------------Solutions 10----------------------------------------------------------------Benefits 11----------------------------------------------------------------
Conclusion 11---------------------------------------------------------------
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Summary Organizations have implemented enterprise applications such as ERP and CRM for business process execution but have failed to address the key enterprise asset: data. In the current economic environment, enterprises that fail to capitalize on their data assets jeopardize their cost structures and their earnings potential. It is vital for organizations to leverage their data assets to measure their business performance, identify the weak poles and strategic improvement spots to scale their business to new heights. Business Intelligence (BI), the recent innovation in IT, has emerged to be a potential hope for the organizations to build a strong business milieu without any new asset investments and utilizing the existing key assets of the organizations. This White Paper describes the best BI practices to be adopted in leveraging the organization's key assets for a dynamic business transformation.
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Introduction Over the years, companies have acquired volumes of data, but much of this data is trapped in multiple, disparate systems which cannot easily communicate. As a result, firms must expend considerable effort to tap into the full potential of these data assets to strategically maneuver the business in a rapidly changing and competitive marketplace. The latest evolution in IT is "Business Intelligence (BI)," which promises to help businesses better tap into and leverage their data assets. Business Intelligence provides the mechanism for people in organizations to examine historical trends, to measure results, to look for patterns in the data that might be missed in standardized reports and event to bubble alerts when certain conditions are or aren't met.
Methodologies Business intelligence expands across a breadth of methodologies and tools in various categories. The methodology and tools are not nearly as important as the vision and execution of a business intelligence strategy for the enterprise. However, to organize thought around what comprises business intelligence is categorized into Data Collection (the gathering of data), Information (transformation of data to understand its meaning), and Vision (the capacity, governance, and process to do something with the information). These examples are not by any means all encompassing, but are provided to demonstrate BI's scope.
Data Collection
. Executive Information Systems . Enterprise Management Systems . Management Information Systems . Portals . Dashboards . Score carding . Online Analytical Proc... [download for more]
