Big Data has allowed organizations to make significantly better evidence-based decisions than ever before. However, with so much information, a new challenge for us is to rank all the possible actionable hypotheses. There is good news on this front because many organizations have shown that it is possible to introduce controlled (A/B) experiments into business intelligence processes.
But enhancing your organization's business intelligence process maturity level to include A/B-based testing, particularly in a Big Data environment, requires new underlying technical and business capabilities – and cultural shifts. This class reviews the foundations of A/B testing and presents several case studies of successful and failed applications of A/B testing in a Big Data setting. This will help you apply sound A/B testing into your data-driven organization. Attend this class to learn:
- How other organizations are utilizing A/B testing
- Best-practices for applying A/B testing
- Where to place your organization in an A/B testing inclusive maturity model
- Methods to introduce A/B testing into your environment