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The Stability of Customers' Sentiment, Satisfaction and Recommendation Intentions

Businesses assess the attitudes of their customers using customer surveys. The purpose of these surveys, typically conducted annually, is to help companies maintain or improve the quality of the customer relationship. The quality of the customer relationship is typically indexed by a few key questions, each measuring something important about the health of the customer relationship. These […]

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When Does Education Level Matter in Data Science?

Data scientists are highly educated. In our study of data scientists, we found that over half of them, both men and women, hold either a Masters or PhD degree and about a quarter of them hold a 4-year degree. The level of educational attainment is related to proficiency in data science skills (more advanced degrees […]

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The Hype of Big Data Revisited: It's About Extracting Value

Over a year ago, I tested the claim that Big Data was the most hyped technology ever. Using Google Trends, I compared the term "Big Data" with "Web 2.0" and "cloud computing". It turned out that the Web 2.0 and cloud computing were more hyped than Big Data (as measured by number of searches on the topics). At […]

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Maximizing the Impact of Data Science Using the Scientific Method

We live in a Big Data world where everything is being quantified. As a result, businesses are trying to make sense of their ever-expanding, diverse, streaming data sources to drive their business forward. If your competitors have access to the same type of data (CRM, ERP, weather, etc.) that you do, how can you keep ahead […]

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How IBM is Transforming Data Science

I am at the IBM InterConnect 2016 event in Las Vegas. While this event, IBM's largest (estimated 24,000 attendees!), is billed as a cloud and mobile conference, sessions focused on a variety of related solutions around analytics, security, DevOps (which I learned is a methodology) and Watson Internet of Things. I was invited by IBM as […]

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For Data Scientists, Big Data is not so Big

In our study of data scientists, we found that only about a third of them possessed skills needed to handle big and distributed data. These results are in line with findings from other studies that find that data scientists typically analyze small data sets. We examined the proficiency of data scientists across 25 different data science skills. […]

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The Most Important Skill in Data Science: Mining and Visualizing your Data

While data scientists have many resources in their tool belt, our research shows that proficiency with data mining and visualization tools consistently ranks as one of the most important skills in determining project success. We used two methods to rank data science skills. The first way was based on the frequency with which professionals possessed the skills. This method identified data […]

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