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With the economy suffering and global competition increasing, businesses need every decision to count more than ever. From a big picture look to practical applications, business intelligence can help businesses improve the speed, quality and accuracy of their decisions, whether related to long-term strategy or day-to-day operations.
The goal of business intelligence (BI) should be to assist business in maximizing the value of their data. Whether companies know it or not, their data is one of their most valuable assets for strategic and operational decision-making. When done right, BI has the potential to deliver highly relevant, highly targeted applications, reports and dashboards designed to maximize an organization’s ability to gain specific, actionable knowledge from their corporate data. That translates to valuable tools such as statistical analysis, predictive analytics and cross-referencing data from different departments to mine for trends. But when done wrong, BI has the power to create organizational, political and technical debacles of Biblical proportions.
So, how do you navigate the minefield of complex topics like business intelligence? What about important supporting topics such as data warehousing, data governance and data stewardship? How do you make sure that the decisions your organization is making are the best possible ones—data driven, insightful and packed with value for your business? The first step is to know what you shouldn't do if you want your BI initiative to succeed.
Myth: The technology is the hard part.
Many see business intelligence or data warehousing as technology problems. They get budget and approval, do lots of research, have vendors give demos and promise endless mentoring … all in the industrious (if misguided) attempt to “buy” business intelligence.
Unfortunately, BI is not, and likely won’t be soon, a technology platform. It doesn’t come shrink-wrapped—at any price. It can’t be bought from anybody. BI is a new way of thinking, best practices molded by nearly two decades of successes and failures, architectural paradigms for data and software, changes to your organization, overcoming political hurdles and much more. The truth is that the technology is actually the (comparatively) easy part.