This is a transcript of a webinar hosted by InetSoft entitled "Why Self-Service BI?" The speaker is Mark Flaherty, CMO at InetSoft.
Mark Flaherty (MF): Traditionally most business users have had to rely heavily on IT to get access to information the need to make business decisions. This not only causes inordinate delays in decision-making, but also places extra dependencies on IT. This has increased the overall cost of business intelligence. All of these factors translate into higher operating costs, reduced productivity, customer dissatisfaction, and most importantly a higher level of dissatisfaction among employees of an organization, both in IT and in the business.
To maximize competiveness, enterprises have to adopt ways in which business users can quickly and easily get the required information. So self-service BI describes a business intelligence environment in which business users can get rich, right, and real information as easily as they get information from a Google search. In other words, it has to be as intuitive and quick to get results as the common Internet search engine.
For this to happen, in an ideal world, business and IT need to work together to create a self-service BI environment that enables business users to access information with close to zero support from IT for their day to day operations. Naturally doing this increases the overall ROI of a BI implementation.
The need for such self-service BI has become less of an aspiration and more of a requirement in today’s world. We are definitely seeing a trend towards self-service BI. It really is important that IT can focus on other critical issues while the users can just access information independently.
Most large organizations have multiple, inconsistent BI applications. And a single data warehouse does not adequately cover the needs of all lines of business. This is because the data warehouse was developed independently in a departmental silo. This prevents business users from have access to consolidated business data and metrics.
In fact, in many large enterprises, one single data warehouse would not be able to meet the needs of the entire company. If a single data warehouse does not adequately cover all lines of business, then users will have to combine data from different sources and consolidate them on their own, usually in a spreadsheet, which leads to several spreadmarts within the same organization.
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