1. Driving User Adoption
A large part of successful BI implementation depends on how it is received by end-users. Organizations must keep in mind that no matter how well a BI tool is built and implemented, the end-user is the decision maker in most cases. They must consider these factors and resolve any issues that the user might have before he even realizes the problem existed. For example, user involvement in design can increase adoption and encourage them to become advocates for future expansion.
2. Justifying BI Investments
Traditional BI solutions are based on the development of large IT infrastructure, and fail to deliver information efficiently. Upgrading from traditional BI to more agile dashboard solutions will require additional investment and changing existing business processes. When implemented properly, BI projects can help an organization improve business agility, drive down operating costs and increase customer satisfaction.
3. Adapting to Big Data
Enterprises must build a strong foundation that can manage increasing data volumes, rapidly expanding user bases, different data types as well as support the integration of additional data sources effectively. We are witnessing a tremendous increase in data volumes being analyzed and stored in data warehouses across the globe. This data can provide advanced analytics, which means that existing BI architectures must evolve to meet the demands generated by big data.