Continuing with the theme of business / IT partnerships, another example I’ve been involved in is integrating business data into an IT managed environment – in this case, an enterprise data warehouse.
A great example of business and IT working together to innovate is in the development of operational analytics. As data volumes and frequency of data continue to increase, organizations have realized that it’s not enough to analyze their data – they must take action on it.
Many consultants have come across unexpected data conditions while deep into the development or testing phase of a data integration effort. Unfortunately, the need for a major shift in architecture or approach is sometimes identified soon after a system is implemented into production. Upon discovering this type of situation, you likely experience a sinking feeling, knowing the potential negative consequences. You imagine blown budgets, missed deadlines, loss of credibility with the business, and unpredictable results. You begin analyzing what caused the problem, how it could have been avoided, and who is at fault
We all know that ‘bad data’ is bad, but to what extent? Have you ever been a part of an email campaign where you get more email bounce-backs than successfully sent messages? While the annoyance factor is high, research tells us it can’t compare to the true cost of having customer data that’s out of date, duplicated, or inaccurate. As a frame of reference, think about the grocery store loyalty cards in your wallet. Do you always have them with you when you