PAKISTAN BUSINESS REVIEW - Institute of Business Management

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Business Intelligence: A New Dimension to Business Market Report Initiation - Building reference data – Extract from sources – Validate – Transform – Load into stages tables – Audit reports – Publish – Achieve - Cleanup Effective data ETL processes represent the number one success factor for data warehouse projects and consume 70% of the total time spent on the project. Data extraction also takes time depending on the complexity of source systems. The data extraction strategy can be defined by considering sources identification, extraction method (manual or tool based), extraction frequency (daily, weekly, quarterly etc.), time window for extraction process, and job sequencing and exception handling for input records that cannot be extracted. Inmon (1995) defined a data warehouse as a centralized repository (collection of resources that can be accessed to retrieve information) of an organization’s electronically stored data, designed to facilitate reporting and analysis. Inmon (1995) is one of the leading proponents of the top-down approach to data warehouse design, in which the data warehouse is designed using a normalized enterprise data model. A data warehouse is a subjectoriented, integrated, time-variant and non-volatile collection of data in support of management’s decision making process. The top-down design methodology generates highly consistent dimensional views of data across data marts since all data marts are loaded from the centralized repository and also proven to be robust against business changes. Generating new dimensional data marts against the data stored in the data warehouse is a relatively simple task. The main disadvantage to the top-down methodology is that it represents a very large project with a very broad scope. Kimball (2002) has given the bottom-up approach where data marts are first created to provide reporting and analytical capabilities for specific business processes. Data marts contain, primarily, dimensions and facts. Facts can contain either atomic data and, if necessary, summarized data. The single data mart often models a specific business area such as sales or production. These data marts can eventually be integrated to create a comprehensive data warehouse. PAKISTAN BUSINESS REVIEW JULY 2011 402
Market Report Business Intelligence: A New Dimension to Business Data Mart: To improve the query performance, a partitioned sector of the overall data warehouse is known as Data Mart. The emphasis of a data mart is on meeting the specific demands of a particular group of knowledge users in terms of analysis, content, presentation, and ease-of-use. Data marts are designed to support business function like sales, marketing, finance, inventory, HR, production etc. In general, a data warehouse tends to be a strategic but somewhat unfinished concept; a data mart tends to be tactical and aimed at meeting an immediate need. Meta Data: Meta Data is the data about data. It is basically a data dictionary which acts as the glue that connects all the part of the data warehouse. Metadata can be stored and managed in a database, often called a registry or repository. It provides information about the contents and structures of data, such as means of creation, purpose of the data, time and date of creation, creator or author of data, placement on a network (electronic form) where the data was created, what standards used etc. Organizations are increasingly using of business intelligence to identify cost saving opportunities and to improve quality of products and services as a way to beating the competition. There are many categories of tools available in the Business Intelligence market from simple query and reporting to complex performance management and advanced visualization systems. Business Intelligence vendors are now also consolidating tools in every category to provide complete business intelligence solutions to companies. However, some organizations still prefer to have a ‘best of bread’ strategy in which they select Business Intelligence tools in each category from different vendors. i. Query & Reporting: It is the process of putting a query to database, then formatting it to create a report. There are two types of reporting, 403 PAKISTAN BUSINESS REVIEW JULY 2011
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