We are taking Wait List registration because dinner seats are SOLD OUT. Meals may not be available, however, "Presentation-only" seats are still available.
Agile methodologies such as Scrum are popular and effective approaches to software development that focus on creating a high value, maintainable product quickly through iterative development and close collaboration between the team and the customers. This approach enables rapid delivery and development along with flexibility and a focus on delivering high value features. Agile methodologies are used everywhere from start-ups to the Department of Defense. These methodologies work great for standard software development… but what about Data Warehousing projects? This presentation will address the hotly debated topic of how well these approaches fit Data Warehousing, why many people fail, and what you can do to succeed and reap the benefits.
What You Will Learn
This presentation will provide real world examples, learnings and strategies for using an Agile methodology to build an Enterprise Data Warehouse. The talk will focus on using Scrum (one flavor of Agile) that is well suited to the task.
The topics we will cover include:
- What Agile is
- When you want to use Agile
- What you need in to do for it to be successful
- What common challenges you will need to consider
David Darden is a Business Intelligence professional specializing in enterprise reporting, analytics, data warehousing, performance management and Agile methodologies. He has spent 16 years working in the technology industry with companies ranging from start-ups to Fortune 50 companies. David has spent the last 10 of those years focusing on using Agile methodologies to deliver high quality Business Intelligence projects across numerous industries.
David joined Big Fish, the world's largest producer of casual games, in 2010. Since that time he has been a technical lead, manager, and Scrum Master for the Big Fish Business Intelligence team. The Business Intelligence team at Big Fish is responsible for building and maintaining the Enterprise Data Warehouse, performing advanced analytics, and creating analytic applications used by all parts of the organization.