Anaconda’s State of Data Science 2021 report, released July 29, looks at how data science is evolving as a field, the business environment and overall trends in adoption by academic institutions, as well as what students can do to prepare for the future.
This year’s State of Data Science report brings together insights from more than 4,200 respondents to delve into data science industry trends such as the impact of COVID-19, popular programming languages, data literacy, and bias and interpretability in machine learning models.
In this year’s online survey, Anaconda received more than 4,200 responses from individuals using data science and machine learning tools in more than 140 countries/territories.
The impact of the pandemic on data science
COVID-19 has affected almost every industry — from health care to government, financial institutions and more; They all need ways to quickly collect data, process it, and find solutions to new problems.
Q1: Has the COVID-19 pandemic affected your organization’s investment in data science?
A1: When asked how involved their roles are in business decisions, 14% of respondents stated that “all” decisions are dependent on the insights they or their teams explain, and 39% stated that “many” business decisions are dependent on them.
Among business organisations, 50 per cent said their investment in data science had stayed the same or increased during the pandemic, while 37 per cent said it had decreased.
Data work and the future of work
A common theme in the news today is that automation is taking over and eventually replacing human workers. However, the results show that automation is gaining popularity in data science and is not seen as a competitor, but as a complementary tool for practitioners.
Q2: What do you think of automation or AutoML?
A2:55% of respondents want to see more automation and AutoML in data science, while only 4% are concerned about how automation will affect data science.
Enterprise adoption of open source
Using and contributing to open source software (Python/R libraries such as Pandas, NumPy, etc.) is a key differentiating factor for the most innovative organizations. Organizations can save significant time and resources by using open source software.
Q3: Does your employer encourage you and your team to contribute to open source projects?
A3: Most respondents said that their employers are empowering them to contribute to open source by increasing the funding associated with the development of open source projects.
PYTHON’s popularity
Q4: How often do you use the following languages?
A4:63% of respondents said they always or often use Python, making it the most popular language in this year’s survey. In addition, 71% of educators are teaching Python, and 88% of students report teaching Python in preparation for entering the data science/machine learning field.
Python is becoming an increasingly popular programming language for data scientists, researchers, students, and professionals around the world.