Bob Hayes
Machine Learning Adoption Rates Around the World
A worldwide survey of data professionals showed that adoption of machine learning methods in their company is 45%. Twenty-one percent of survey respondents said their employer is exploring ML methods. ML adoption rates varied by country with Israel (63...
Data Professionals Use of Analytics and Business Intelligence Tools
Data professionals prefer analytics tools over business intelligence tools when getting insights from their data. Nearly half of data professionals surveyed in Kaggle’s 2020 Data Science and Machine Learning Survey said they do not use BI tools. The to...
For Data Professionals, Python Remains Top Programming Language while R Continues to Decline
Data professionals of all stripes, including data scientists, machine learning engineers and others, use different types of tools in their jobs. A recent survey of over 20,000 data professionals by Kaggle revealed that Python, SQL and R continue to be ...
Who Does the Machine Learning and Data Science Work?
A survey of over 19,000 data professionals showed that nearly 2/3rds of respondents said they analyze data to influence product/business decisions. Only 1/4 of respondents said they do research to advance the state of the art of machine learning. Diffe...
Top Tools Used by Data Professionals to Analyze Data
Analysis of usage of 5 primary tools used to analyze data showed that the top tool used by data professionals to analyze data are local development environments (54%), followed by basic statistical software (20%), cloud-based data software and APIs (8%...
Top Machine Learning Algorithms, Frameworks, Tools and Products Used by Data Scientists
A recent survey by Kaggle revealed that data professionals used a variety of different algorithms, tools, frameworks and products to extract insights. Top algorithms were linear/logistic regression, decision trees/random forests and Gradient Boosting Machines. Top frameworks were Scikit-learn and TensorFlow. Top tools for automation...
Most Popular Integrated Development Environments (IDEs) Used by Data Scientists
Results of a worldwide survey of data professionals, the top used Integrated Development Environments (IDEs) are: Jupyter (73% have used), Visual Studio (31%), RStudio (30%), PyCharm (29%) and Notepad++ (22%). Integrated Development Environments ...
Usage of Programming Languages by Data Scientists: Python Grows while R Weakens
The practice of data science, including work in machine learning and artificial intelligence, requires the use of analytics tools, technologies and programming languages. A recent survey of nearly 20,000 data professionals by Kaggle revealed that Pytho...
Customer Experience and Emerging Technologies: My CXChat Summary on Artificial Intelligence, Machine Learning and...
Below is a list of topics, answers and articles in support of a recent Tweet Chat in which I was the guest. The chat (#CXChat) was on customer experience and emerging technologies. I was invited as a guest in a weekly tweet chat that is…
Top Cloud Computing Products and Services Used by Data Scientists
A recent survey revealed that 69% of data pros have used at least one cloud computing product in the last 5 years while 62% of data pros have used at least one cloud computing service in the last 5 years. The most popular cloud computing…
Most Popular Machine Learning Frameworks and Products Used by Data Professionals
A recent survey revealed that 84% of data pros have used at least one ML framework in the last 5 years while 51% of data pros have used at least one ML product in the last 5 years. The most popular ML frameworks include Scikit-Learn,…
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 t...
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...
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 ...
Data Science and the Quest for Truth
I was interviewed by IBM to share my thoughts on a topic related to data science about which I’m passionate: How do we know what we know and, once we know it, how do we know it’s the truth? IBM turned that interview into a comic…
Customer Success Executives Need to Answer These Three 3 Critical Questions
In today’s subscription-based economy, customers are no longer trapped in long-term contracts; instead, they are able to jump to competitors easily when they become dissatisfied with their current vendor. Consequently, many subscription-based and SaaS ...
4 Reasons Why Customer Retention Matters to Your Customer Acquisition Efforts
Business growth depends on acquiring new customers and keeping them around for a long time. Yet businesses are over 2x more likely to focus on acquisition efforts than they are retention efforts. In today’s post, I want to discuss why busines...
Salaries of Data Scientists and Machine Learning Engineers From Around the World
Annual salaries for data scientists and machine learning engineers vary significantly across the world. Based on a 2017 Kaggle survey of data professionals, countries with the highest paid data scientists and machine learning engineers (in USD) were: U...
Top 5 Paying Data Science and Machine Learning Jobs in the US
A recent survey by Kaggle revealed that the annual median compensation (salary + bonus) of data professionals in the US was $118K. US data professionals who self-identified as machine learning engineers, software developers and data scientists had the ...
My Highlights from IBM Think 2018: Data Science, SPSS, Augmented Reality and the Customer...
I attended IBM’s inaugural Think event in Las Vegas last week. This event, IBM’s largest (estimated 30,000+ attendees!), focused on making your business smarter and included keynotes and sessions on such topics as artificial intelligence, data science...