Putting Big Data Self-Service Analytics in the hands of Business People

Enterprise Analytics are currently often the purview of a narrow group of data scientists and trained analysts, with business users bottlenecked by those experts, or left to rely on static BI dashboards that are too slow for data exploration, but the economy increasingly demands that front-line business decision makers need real-time self-service analytics to make decisions faster and improve the customer experience. In this talk, Peter Kacandes, a Sr. Technical Product Marketing Lead at Imply.io, will discuss: The origins of this problem in the architecture of the current analytics tech stack, and the emerging hot analytics technology stack, which opens up self-service analytics on real-time big data to hundreds or thousands of business people at a company. How a real-time data store that is 10-100X faster than data warehouses or data lake query engines, combined with an intuitive and high-speed UI, can empower untrained “citizen analysts” such as marketing, product, and operations managers, to make myriad daily decisions faster and data-driven. The learnings of well-known companies who have implemented hot analytics for use cases such as user behavior, network, application and service performance monitoring, and real-time fraud detection.