Most Used Data Science Tools and Technologies in 2017 and What to Expect for 2018

The practice of data science requires the use of analytics tools, technologies and languages to help data professionals extract insights and value from data. A recent survey by Kaggle revealed that data professionals relied on Python, R and SQL more than other tools in 2017. Looking ahead to 2018, the survey results showed that data professionals are most interested in learning Tensorflow, Python and R. Kaggle conducted a survey in August 2017 of over 16,000 data professionals (2017 State of Data Science and Machine Learning). Their survey included a variety of questions about data science, machine learning, education and more. Kaggle released the raw survey data and many of their members have analyzed the data (see link above).