When companies initially embark on their BI development initiatives, they often underestimate its complexity. Some begin BI in the first place because their packaged applications don’t deliver the reporting functionality they need. Others embark on BI because the data they need to analyze is located in multiple, disparate application systems. While positioning a data warehouse to integrate and store historical data from packaged applications, like ERP or CRM, is a reasonable and proven approach, many companies try to repurpose the development methods associated with these packages to deliver BI.
But comparing development methods and skill sets for these two divergent types of systems is like comparing picking apples to making a fruit salad. The fact is the methodology for building a data warehouse is very similar to traditional code development using lower-level programming languages. To be successful building a data warehouse, a team should have skills in business requirements gathering, functional requirements definition, specification and design, data modeling, database design, as well as all the skills associated with loading the data and coding the application. This is clearly…
When companies initially embark on their BI development initiatives, they often underestimate its complexity. Some begin BI in the first place because their packaged applications don’t deliver the reporting functionality they need. Others embark on BI because the data they need to analyze is located in multiple, disparate application systems. While positioning a data warehouse to integrate and store historical data from packaged applications, like ERP or CRM, is a reasonable and proven approach, many companies try to repurpose the development methods associated with these packages to deliver BI.
But comparing development methods and skill sets for these two divergent types of systems is like comparing picking apples to making a fruit salad. The fact is the methodology for building a data warehouse is very similar to traditional code development using lower-level programming languages. To be successful building a data warehouse, a team should have skills in business requirements gathering, functional requirements definition, specification and design, data modeling, database design, as well as all the skills associated with loading the data and coding the application. This is clearly a complex mix of technical knowledge to deliver a business solution spanning everything from storage allocation to workload management to systems integration to application programming. The fact is you’re building something from scratch.
The packaged application world is complex in its own right, but it’s also very different, as are the skills and methodologies involved in building these environments. Most IT organizations accustomed to implementing packages use third-party firms to install and configure these systems. Their staff members don’t have the necessary skills to build these solutions, and often require training and multiple years of hands-on use to be proficient in supporting these systems. In addition, most organizations forget that implementing their business applications typically takes a year or longer.
When was the last time you were allowed a full year to implement your data warehouse? And was your team even half the size of the packaged app’s development team?
