The growing buzz for business intelligence has developed hand in hand with the ever increasing amounts of data being collected in every sector of the economy. Individual Business Intelligence (IBI) is the process of an Individual deriving insights efficiently through data analysis of self-accumulated data and inherited accumulated data to discover more about the individual, find trends, patterns and correlations and enable better decision making based on facts in order to improve the life of the individual.
Though the term business intelligence is sometimes a synonym for competitive intelligence (because they both support decision making), BI uses technologies, processes, and applications to analyze mostly internal, structured data and business processes while competitive intelligence gathers, analyzes and disseminates information with a topical focus on company competitors.
In many cases it’s the HR data that will be the last to get pulled into a data warehouse because of the sensitive nature of the data but once you start to manage this data effectively, you can see at a glance things like retention, absentees and where people are struggling and this information can prove invaluable when it comes to the effective management of your business.
By providing timely access to trusted information across functions and departments for actionable insight and fact-based decision making, the business intelligence initiative will help inform long-term planning and execution of the university strategy and support GW’s strategic goals of excellence in education, excellence in research and world-class service to all university stakeholders (students, faculty, alumni, parents, staff and community members).
Therefore, when designing a business intelligence/DW-solution, the specific problems associated with semi-structured and unstructured data must be accommodated for as well as those for the structured data. While Developer is developing, QE is already creating the test cases based on test scenarios and also setting up the test data. Well-established tools rather than simple tools could provide such benchmarking.