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Tag Archives | Data science

Figure 1.

Using Predictive Analytics and Artificial Intelligence to Improve Customer Loyalty

As users/customers engage with a company (their products, services, surveys), they generate a lot of data about their behaviors and interactions with the brand. Predictive analytics and artificial intelligence capabilities provide a way to extract insights from that data to help you improve the customer experience and optimize customer loyalty. Artificial Intelligence and Predictive Analytics […]

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Figure 1. Challenges Faced by Data Professionals

Top 10 Challenges to Practicing Data Science at Work

A recent survey of over 16,000 data professionals showed that the most common challenges to data science included dirty data (36%), lack of data science talent (30%) and lack of management support (27%). Also, data professionals reported experiencing around three challenges in the previous year. A principal component analysis of the 20 challenges studied showed that challenges […]

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Figure 1. Favorite Data Science Blogs, Podcasts and Newsletters

Favorite Data Science and Machine Learning Blogs, Podcasts and Newsletters

Over 16,000 data professionals were asked to indicate their favorite data science blogs, podcasts and newsletters.  The top two favorite blogs were KDNuggets and R Bloggers. The top two podcasts were Becoming a Data Scientist and The Data Skeptic. The top two newsletters were O’Reilly Data and Data Elixir. Data professionals use a variety of […]

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Data Days Video Series: What is Data Science?

I like sharing my knowledge about the power of data and analytics. This knowledge can help business leaders and citizens understand how the world works, improving how they manage their business and make better decisions to improve their personal lives, respectively. Toward that end, I am creating a video series called, Data Days, to explore the world […]

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Figure 2. Usefulness of Platforms and Resources to Learn Data Science

Top 10 Platforms and Resources to Learn Data Science Skills

A recent survey of over 16,000 data professionals showed that the most used platforms/resources included Kaggle, Online courses and Stack Overflow Q&A. Additionally, the most useful platforms/resources included Personal Projects, Online courses and Stack Overflow Q&A. On average, data pros used around three (3) different platforms/resources to learn data science skills. There are many ways […]

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Figure 1. Competency in Machine Learning Areas

A Majority of Data Scientists Lack Competency in Advanced Machine Learning Areas and Techniques

Data science requires the effective application of skills in a variety of machine learning areas and techniques. A recent survey by Kaggle, however, revealed that a limited number of data professionals possess competency in advanced machine learning skills. About half of data professionals said they were competent in supervised machine learning (49%) and logistic regression […]

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Figure 2.

How Data Science Helps Customer Success Leaders Answer 5 Important Questions About Customer Churn

Data science methods and related tools (i.g., predictive analytics, machine learning) can help companies improve their customer success programs by answering 5 important questions about customer churn, including what is the current churn/retention rate (e.g., descriptive analytics), who is at risk for churning (predictive analytics), what actions can prevent churn (i.e., prescriptive analytics) and more. […]

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Figure 1. Job Satisfaction Varies by Job Titles for Data Professionals

Machine Learning Engineers and Data Scientists Report Highest Job Satisfaction Among Data Professionals

Results from the Kaggle State of Data Science and Machine Learning survey of data professionals revealed that job satisfaction varies widely across job titles. Data professionals who reported the highest level of job satisfaction were: 1) Machine Learning Engineers, 2) Data Scientists and 3) Predictive Modeler. Data professionals who reported the lowest level of job […]

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