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Tag Archives | Data science

Figure 1. Time spent on activities of data science projects.

How do Data Professionals Spend their Time on Data Science Projects?

Data science projects require data professionals to devote their energy toward different activities toward project completion. Results of a recent study of over 23,000 data professionals found that data scientists spend about 40% of gathering and cleaning data, 20% of their time building and selecting models and 11% of their time finding insights and communicating […]

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Table 1. Principal Component Matrix of 48 Data Science Tools, Technologies and Languages - data from Kaggle 2017 The State of Data Science and Machine Learning survey of data professionals. Click image to enlarge.

Usage-Driven Groupings of Data Science and Machine Learning Programming Languages

Analysis of usage patterns of 16 data science programming languages by over 18,000 data professionals showed that programming languages can be grouped into a smaller set (specifically, 5 groupings). That is, some programming languages tend to be used together apart from other programming languages. A few of the different groupings of languages reflect specific types […]

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Figure 1. Programming Languages used in 2018. Click image to enlarge.

Programming Languages Most Used and Recommended by Data Scientists

The practice of data science requires the use of analytics tools, technologies and programming languages to help data professionals extract insights and value from data. A recent survey of nearly 24,000 data professionals by Kaggle revealed that Python, SQL and R are the most popular programming languages. The most popular, by far, was Python (83% […]

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top102018

Top BOB Blog Posts of 2018: Data Science, Machine Learning and the Net Promoter Score

The importance of data science and machine learning continues to grow in business and beyond. I did my part this year to spread interest in data science to more people. All of my top blog posts of 2018 (most reads) are all related to data science, with posts that address the practice of data science, […]

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Customer Genome Project

How Data Integration and Machine Learning Improve Retention Marketing

Retention marketing is about preventing your valuable customers from churning. Reducing customer churn requires you to know two things: 1) which customers are about to churn and 2) which remedies will keep them from churning. In this paper, I show you how marketers can improve their customer retention efforts by 1) integrating disparate data silos […]

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