There is no silver bullet that will allow us to remove all uncertainty, but we can apply some business intelligence practices to the concept of annual planning to at least increase our confidence levels and reduce the risks around the decisions that we make.
Big Data has become the latest craze within the IT community, revolutionizing business intelligence capabilities. But what is it really--and how will it impact our community? Here are some tips for the PM to evolve with this emerging trend.
In an initial business intelligence project, you run the risk of failure from loss of the initiative’s momentum due to inadequate support from business leaders. What tactics are needed to defeat this loss of momentum?
Inevitably, the intersection of big data and the idea of the quantified self (the hot movement of the moment) is going to show up in project management. Think of it as the “quantified project” where just about everything about a project can be measured, reported on and managed. Arguably, someone may be trying to invent this very thing right now. But should they?
Lessons learned is still a bit of a joke in many organizations, a process that is paid lip service without any expectation that any of the lessons will even be shared. Can we improve things with a little science? One PM believes that we need to address two specific elements...
Successful BI initiatives take more than just people, technology and fancy tools. They require proper levels of engagement of BI teams with key stakeholders; coming to grips with legacy system shortcomings and realities; and a strategically aligned commitment.
Making good business decisions while managing a portfolio often comes down to gathering the proper data and creating useful business intelligence. Here's some advice on four critical stages of the process.
Let’s take a broad look at how business intelligence is used in project management to improve performance and focus efforts on activities that garner positive results--focusing on the two phases that get you the quickest results.
Cloud Computing just might hit its stride in 2013. But while the momentum toward Cloud Computing is consistent within larger organizations, the reasons for the push are not...and not everyone is jumping into the Public Cloud pool.
How do you select the best data extraction/transformation toolset for your data warehouse? Evaluate features, functionality, vendor reputation... the works. Follow the example set by this robust tool evaluation.
Even though you've built the perfect data warehouse, it's better to be safe than sorry if something goes wrong during its operation and you need to restore the original data files. Take the time to document your backup and recovery procedures, as in this example.
Mission-critical projects need to be well-justified, with clear goals that can be referenced throughout the life of the project. This business case template offers an excellent approach to goal-setting and a way to communicate those goals effectively.
Code is a developer's signature on a software project, and not all developers play by the rules of good coding standards. Ensure that your development team leaves a coding legacy that not only implements the application at hand but can be understood by others and maintained during future development cycles.
Are you putting together a data warehouse? This Microsoft Project plan will help you keep tabs on all the complex stages and steps involved in building decision support systems and a knowledge-based applications architecture and environment.