In recent years, the focus of big data analytics has shifted from simple statistical inference to sophisticated Machine Learning algorithms. Machine Learning (ML) can be understood as a set of analytical tools that collectively derive a model based on a set of observations. Simple data modeling is now deemed insufficient because it is based on examining trends in data, but often ignores subtle features and can cause data analysts to miss the “big picture”.Read More >
Spark'ing Scope Creep
I had the fortunate opportunity to present in the disruptive-technology track at the 2015 Rice Oil and Gas HPC Workshop during the first week of March. What I presented during my two-minute drill in this session ended up being much more disruptive than I anticipated.Read More >
This year marks the 10th anniversary of the creation of Hadoop. Over that decade, the open-source software platform has grown into the de facto standard of the big data marketplace. Part of this is due to the overall growth in spending on analytics, which research firm IDC recently said would reach $125 billion this year. But it also is due to the advantages that open-source Hadoop has over proprietary systems.
In December 2014, the online technology community Wikibon issued a report by lead big data analyst Jeff Kelly titled Hadoop-NoSQL Software and Services Market Forecast, 2013-2017. He highlights three problems with traditional database management systems:Read More >
I always wanted to be a seismologist.
Scratch that: I always wanted to be an astronaut. How could I help it? I grew up in suburban London (UK, not Ontario) watching James Burke cover the Apollo missions. (Guess I’m also revealing my age here!)
Although I never gave my childhood dream of becoming an astronaut more than a fleeting consideration, I did pursue a career in science.Read More >
The Summit features 6 tracks. By tapping the expertise of our Hadoop braintrust, we’ve submitted 4 ideas to 3 different tracks. Because we’d like to earn your votes, please allow us elaborate.Read More >