Large-Scale Distributed Analytics: A Research Program

Since starting my part-time appointment as an associate professor at the Australian National University, I have been thinking about spending more time on fundamental research. As Don Knuth counsels, “if you find that you’re spending almost all your time on theory, start turning some attention to practical things; it will improve your theories. If you … More Large-Scale Distributed Analytics: A Research Program

Agile Data Science: A Portfolio Approach to Managing An Analytics Team

I recently concluded a two-year stint managing a team of ten highly skilled analytics professionals spread across three different locations. There were of course many challenges but the team over-achieved on just about every measure of success one can imagine. The team’s wins include completing on-time and under-budget a data-matching project that delivers tens of … More Agile Data Science: A Portfolio Approach to Managing An Analytics Team

Scalable Entity Resolution Using Probabilistic Signatures on Parallel Databases

My colleagues and I have just published on arXiv a simple but highly effective Entity Resolution algorithm that can scale to billions of records and handle significant data quality issues. The paper is titled Scalable Entity Resolution Using Probabilistic Signatures on Parallel DatabasesĀ and it isĀ an extension of our previous paper on linking millions of addresses … More Scalable Entity Resolution Using Probabilistic Signatures on Parallel Databases

The Missing Data Science Language?

Having spent nearly a decade studying the design and implementation of declarative programming languages in a previous life, I get a bit frustrated whenever I see people getting religious about programming languages and platforms. In the data science circle, an active discussion is around Scala (on Spark) vs SQL (on parallelised relational databases). They are … More The Missing Data Science Language?

Agile Data Science: Don’t Let Your Model Die in a Powerpoint Presentation

Most data science projects are doomed to failure before they even start. There are a couple of reasons. The aspiring data scientist and management may be drawn to a sexy problem rather than an important problem. The full range of data required to do a complete analysis may be inaccessible or even non-existent. And even … More Agile Data Science: Don’t Let Your Model Die in a Powerpoint Presentation