We are in the midst of an exciting time. There is an explosion of very interesting data, and emergence of powerful new technologies for harnessing data, and devices that enable humans to receive tremendous benefits from it. What is required are innovative processes that enable the creation and delivery of value from all of that data. More often than not, it is the predictive (what will happen?) and prescriptive (how to make it happen!) analytics that produces this value, not the raw data itself.
Agile software teams are continuously involved in projects that involve rich, complex, and messy data. Often this data represents innovative analytics opportunities. Being analytics-aware gives these teams the opportunity to collaborate with stakeholders to innovate by creating additional value from the data. This session is aimed at making Agile software teams more analytics-aware so that they will recognize these innovation opportunities.
The trouble with conventional analytics (like conventional software development) is that it involves long, phased, sequential steps that take too long and fail to deliver actionable results. This talk will examine the convergence of the following elements of an exciting emerging field called Agile Analytics:
•sophisticated analytics techniques, plus
•lean learning principles, plus
•agile delivery methods, plus
•so-called "big data" technologies
•The analytical modeling process and techniques
•How analytical models are deployed using modern technologies
•The complexities of data discovery, harvesting, and preparation
•How to apply agile techniques to shorten the analytics development cycle
•How to apply lean learning principles to develop actionable and valuable analytics
•How to apply continuous delivery techniques to operationalize analytical models