Modeling

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]

dashboard / shutterstock

Decisions was initially focused on providing an OEM engine for companies in products like Central Logic Core, RCx Rules, CareFamily and Aviacode – everything from medical coding to claims pre-processing and more. More recently they have begun to sell to end user companies.[read more]

Automated data mining?

Can data mining be automated? To find an answer, we need to analyze the different phases of data mining and estimate which one can be automated. For this purpose, I have chosen the CRISP-DM methodology (I guess any other data mining process would lead to similar conclusions).[read more]

predictive analytics / shutterstock

A couple of weeks ago I attended Predictive Analytics World (#PAWCON), where much of the discussion surrounded “big data” and how to leverage analytics within environments that contain large, complex, and real-time related data. Here are some of the takeaways.[read more]

data visualization

Data analysis is becoming a bigger part of more people's lives. No matter what our profession or background, we can all benefit from data visualization – a key aspect of data discovery software – to help us tell compelling stories, ask and answer more questions, and take the right actions.[read more]

Predictive modeling / shutterstock

Anyone can build a bad model, but to build a good model, don’t we need to know what the algorithms are doing? The answer, of course, depends on the role of the analyst. I contend, however, that for most predictive analytics projects, the answer is “no.” But that's not the whole story.[read more]

Data visualizations

Which of these data visualizations is best? Re-usable in other contexts? What about videos showing growth over time, or more sophisticated graphs where link thickness represents "Internet highway" bandwidth or speed? Let us know what you think in the comments.[read more]

Business Intelligence

How do you assess the overall health and maturity of your Business Intelligence Initiative? This article is the first in a series that reviews the topics to be considered when reviewing the current status of a traditional Business Intelligence initiative.[read more]