Interest in agile BI is high, but adoption and success rates are lagging behind. The lag occurs primarily because agile methods that evolved for software development don’t necessarily fit the needs and complexities of BI projects. The foundations of agile software projects—people and methodology—are important for BI projects but more is needed. BI projects, for example, can’t realistically minimize documentation because knowledge transfer is an essential part of BI success. Requirements discovery is valuable for BI projects, but source data is filled with the unexpected so we also need data discovery. Test-driven development is challenging for BI projects without the help of test automation tools.
In addition to people and methodology, agile BI needs enabling technologies for data discovery, painless documentation, test automation, versioning and change management, rapid deployment, adaptable infrastructure and more. The technologies are available today. Now we need to make them part of the agile toolkit.
You Will Learn
- How data virtualization contributes to agility and success rates of BI projects
- How data warehouse automation resolves challenges and improves agile BI capabilities
- How cloud services increase agility and mitigate risks of agile BI projects
- BI program and project managers; BI technology architects and implementers; anyone seeking to overcome the challenges of using agile methods for BI projects.