Big data analytics as a service: Exploring reuse opportunities

As data scientists, we live in interesting times. Data has been the No. 1 fast growing phenomenon on the Internet for the last decade. Big data analytics have the potential to reveal deep insights hidden by big data that exceeds the processing capacity of existing systems, such as peer influence among customers, revealed by analyzing shoppers' transactions, social and geographical data. In the past 40 years, data was primarily used to record and report business activities and scientific events, and in the next 40 years data will be used also to derive new insights, to influence business decisions and to accelerate scientific discovery. The key challenge is to provide the right platforms and tools to make reasoning of big data easy and simple. In this keynote talk, I will explore reuse opportunities and challenges from multiple dimensions towards delivering big data analytics as a service. I will illustrate by example the importance and challenges of utilizing programmable algorithm abstractions for many seemingly domain-dependent data analytics tasks. Another reuse opportunity is to exploit unconventional data structures and big data processing constructs to simplify and speed up the big data processing.