Data Warehousing and Business Intelligence

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Data warehousing can serve two functions for business intelligence: provide information to help create long-term strategies for a company and provide information to end users for day-to-day operational exercises. Because of the nature of the two functions: analysis and operational, it might be hard to image a data warehousing system that can accommodate both, but it is possible. In order to leverage a data warehousing project to do both, a company must understand what information is required for each.

Business Intelligence for Analysis

Usually, business intelligence is set up to support the decision-making process and will answer these questions for a company: “How is the sales department doing,” “What products have the most sales,” and “What region has the best sales and which has the worst?” The answers to these types of questions then help management make important decisions for the company by giving them an overall view of where the company is headed. This data needs to be more aggregated and has to have enough history to provide meaningful information.

Business Intelligence for Operations

More recently, business intelligence has been used to help salespeople, customer service representatives, and customers from day to day. The data used to provide services for these users must be updated constantly and should be integrated. The questions this type of business intelligence answers are “What are the most recent transactions,” “What has been processed, what hasn’t,” and “What is the best course of action for this customer based on their history?” The high-level information that can be gathered from more traditional business intelligence is far less important than the details and recent history for operations. This type of data can help salespeople make tactical decisions, improve the efficacy of customer service, and increase customer knowledge and satisfaction.

For companies who want both business intelligence for analysis and for operations, there is a way to organize their data warehousing projects to support each activity. Data from all sources must go to a centralized warehouse to be cleansed, have business rules applied, and integrated. Once in the central data warehouse, the data can then be redistributed to different data marts to serve different purposes. This model eliminates issues with duplication, data quality, and data control. This solution can be created from scratch by a company’s IT team or the business could save time and money by finding a business intelligence software company that has already created software for this model. Either way, any company can have it all with this data warehousing model.

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