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Big Data Week Community


How Your Data Can Turn Black Friday into a White Christmas

How your data can turn Black Friday into a White Christmas Returns are a huge area of concern for many retailers; indeed, the sale has not been completed until the customer actually decides to keep the product. But with Black Friday around the corner, and all of the flash buying that entails, can you predict what products are going to cause you the most problems, or even each which customers could give you a headache?


Publishing in a Time When Data Is All Around You

For one, the common knowledge is that you’d have to be really big in the publishing universe to use such tools. Secondly, most people, Marcello Vena thinks, don’t understand the difference between analyzing big data and “normal” data. He distinguishes three key features that set these two kinds of analysis apart. Big data uses a very large volume of unstructured data that standard database management systems simply cannot cope with. Big data needs “adequate data-centric processes from capture, ingestion and curation to search, modelling, analysis and visualization, not to mention other critical operations like storage, maintenance, sharing, transfer, security and availability.” Big data looks at all (or most of) the available information and doesn’t sample it to make it more […] Continue Reading


Playing the Big Data Game – 5 Things You Need to Know About the Games of the Future

We’re in the golden age of gaming. In the US, more than half the households now own a console. Tablets and smartphones are packed with games. The video game market has already topped the movies and music markets. From a juvenile distraction to a mostly grown-up entertainment, this momentum is not about to dissipate. If anything, with the help of big data, it’s increasing faster than ever. You probably don’t know what this is. It’s called the Brown Box, and it’s the grandfather of all game consoles. The prototype was built in 1967 by a man named Ralph Baer. The basic traits of a console are there and have never changed: multiplayer controls and a variety of games to choose […] Continue Reading

Beating Addiction with Big Data

In a previous post, I wrote about the various applications of big data insights in the gambling industry, from tailored marketing initiatives to odds calculation. However, the very same data used to great commercial effect by gambling companies could have another utility: protecting customers from addiction. Gambling brands are under increasing pressure to either relinquish their data insights to independent regulators or take internal measures to protect their customers. But what exactly is being proposed? And how precisely can big data analysis be used to combat problem gambling? New research and innovative safeguards A recent Wall Street Journal article explored the efforts of addiction scientists and industry consultants to spot ‘high-risk’ players through analysis of customer-tracking information. Working in collaboration […] Continue Reading

Becoming a Data Scientist: What a Data Scientist ISN’T

If you’re reading this you probably already have an inkling of what a data scientist is. Have you ever considered what a data scientist isn’t? According to Vincent Granville, author of Developing Analytic Talent: Becoming a Data Scientist, data scientists are: Not statisticians Not data analysts Not computer scientists Not software engineers Not business analysts Data scientists do have some knowledge in each of these areas but also some outside of these areas. NEITHER STATISTICIANS NOR DATA ANALYSTS: One reason the gap between statisticians and data scientists has grown over the last 15 years is that academic statisticians, who publish theoretical articles (sometimes not based on data analysis) and train statisticians, are… not statisticians anymore. Also, many statisticians think that […] Continue Reading


Communication – How to Optimise Businesses

What moves faster the denser you go into it…communication My name is Simon Lavender a Data Scientist at Hunterlodge Advertising (and yes, I came from a science background).   Standardising methodology, using communication allows for better reinvestment of time…it is time that is a finite resource and in an ever more open world, competition is just as large. However, from a background initially in charity (having graduated in Quantitative Genetics) I realised it was the awareness that was key…for 10 years you could go travel an inefficient way to work, then realise a better way.  To you, that route was fine/adequate/efficient, amongst other reasons you didn’t have time to consider it.   Step back, challenge the status quo.  Reflect and consider […] Continue Reading


Consilient Data in the Next Phase of Data

It was after talking with Mark Madsen at Strata that the idea of Consilience really took hold. (At that point, I didn’t know the word, just the idea). There were various iterations of the idea using words such as ‘interoperable’ and ‘compose-able’ but there was nothing satisfying enough to make the idea stick. It finally all came together one evening talking to Nick Harkaway on Twitter to quote “@CodeBeard (Interesting word here might be “consilient”)”. The word Consilient is usefully defined as ‘the principle that evidence from independent, unrelated sources can “converge” to strong conclusions’.  It was the title of a book by E.O. Wilson in discussion of the unification of science. Consilience literally means ‘jumping together’.   IRT Data? At DataShaka we […] Continue Reading

Look Who’s Doing Big Data in Nova Scotia: Matt Hunter, Health Outcomes Worldwide

What kind of data are you working with? Our data primarily describes wound care. Our clients record various metrics relating to wounds, and the treatments of those wounds. What kinds of analytics are you using? We use a custom reporting system to help our clients identify trends and/or issues with wound care. What are the problems your company is interested in solving? We strive to improve the quality and efficiency of wound care by identifying issues in the data. The traditional method of recording all of this data on paper charts makes it hard or impossible to derive conclusions from that data over time. By making it as-easy-as-paper for nurses to collect this data electronically, we can provide deep insights […] Continue Reading

Look Who`s Doing Big Data in Nova Scotia: Tim Webster, Nova Scotia Community College

What kind of data are you working with? Geomatics, lidar elevation What kinds of analytics are you using? Terrain modelling, flood inundation, hydrodynamic modelling. What are the problems your company/project/group is interested in solving? Accurate depiction of the coastal zone and earth’s surface to support models. How did you get involved in your line of work? Geomatics education. What are you most proud of in your work? Employing and developing HQP, advancing the knowledge of laser scanning methods and processing to derive useful products for Nova Scotians. What are the biggest challenges in your line of analytics? Data volume and computer speed, cleaning and processing the lidar point clouds. What’s the best advice you can give someone interested in getting […] Continue Reading