Modeling

Big Data growth / shutterstock

Predictive analysts usually think of doing predictive modeling on structured data pulled from a database, probably flattened into a single modeling table by a query so that the data is loadable into a software tool. We then clean the data, create features, and away we go with predictive modeling.[read more]

Big Data world / shutterstock

When working with familiar data and problems, your confidence in, and the validity of, the assumptions made are probably fairly sound. But if you're doing a new type of analysis or using a data source for the first time, your assumptions may be introducing risk into your decision-making.[read more]

Via Science

Big Math, to Via Science, is “the use of leading edge mathematics on very large supercomputing platforms to make better predictions, recommendations, and explanatory models of how the world works directly from data” and this is where they see themselves.[read more]

Big Data Analytics: what do your Likes reveal?

Big Data Analytics allow us to automatically analyze digital records such as our updates, photos and ‘Likes’ on Facebook. But did you know that your 'Likes' on Facebook could expose intimate details about you as well as personality traits you might not want to share with anyone?[read more]

What does a good analytics vendor look like?

Let’s face it: the best way to make your organization more data-driven is to get the best analytics talent within your organization. So what should you look for in your analytics vendor?[read more]

the analytical life cycle / shutterstock

Analytic skills shortages are not the only reason to focus on decision requirements if you are focused on predictive analytics and data mining. In fact decision requirements modeling has a role in the analytic lifecycle more generally.[read more]

Data warehouse lemmings?

Why do data warehouse projects fail? This, to me, is an interesting yet baffling subject – especially in this day and age – since we possess the tools, methods and skills to deliver them quickly and successfully, but so many still manage to fail. So I’ve gathered a few facts for you to ponder.[read more]

How can Big Data deal with social risk?

Corporations are faced with literally millions of potential threat sources given how the social aspect of today’s online world has empowered practically every individual with immediate reach and influence to broadcast their disappointment, displeasure or disgust with a brand.[read more]

missing data values / shutterstock

Missing data can be a pain; having missing data and not knowing where it is can be even more of a pain. Here is a quick tip for potentially handling missing values during an ETL process, or during any data processing step, and how to quickly spot them.[read more]

data variety / shutterstock

Data variety stands out from the three Vs of big data from the report of the big data survey conducted by NewVantage Partners in 2012. One of the survey results shows companies focusing more on data variety instead of data volume both now and in the next three years.[read more]

Big Data journey / shutterstock

While much around big data remains hype, many companies are in the fledging stages of drawing value from their big data corpus, and given an army of discussions and opinions around the topic, it’s still hard to find a clear roadmap to arrive at the Big Promise.[read more]

Big Social Data

From eating and drinking to watching entertainment to reading, just to name a few, the social conversations of consumers often reveal tremendous insight on their interests, activities, likes, dislikes, attitudes and behaviors simply as a byproduct of their ‘off-line’ engagements while engaging online.[read more]

perception gap

Consumers believe Sears is just for tools and electronics; is this the perception Sears wants to portray? What is Kroger doing better than others are? Walmart tweets way more frequently than other brands, and consumers reciprocate. 4 brands, 1 week and 100,000 Tweets: this infographic lays it all out for you.[read more]

Facebook & big data analytics

Facebook has massive data analytics capabilities and it has a lot of data - big data. It has our personal details, our likes, our updates, our pictures and videos. However, my big question here is: are they overstepping the mark by exploiting this (even very personal) data?[read more]

Anthony Goldbloom, Founder and CEO of Kaggle (Image courtesy of Kaggle.com)

What do brilliant data scientists, roller derby enthusiasts, and Prince William lookalikes have in common? You can find all three at Kaggle, a company whose mission is to bring together the top data scientists in the world to solve complex problems. Anthony Goldbloom is the company’s founder and CEO.[read more]