Data science has long been the domain of hardcore data professionals who understand the complex frameworks and languages involved, but those professionals are in notoriously short supply.
Fortunately, the landscape of tools and frameworks is constantly evolving, and in 2023 I predict new developments that will alleviate challenges for data teams and businesses alike.
On the one hand, the long-heralded citizen data scientists will finally play a greater role in analytics thanks to sheer necessity and a simplification of the tools and platforms involved. On the other hand, data professionals will start to benefit from some of these simpler tools to accelerate their work and a push for greater standardization will help the industry as a whole.
Data science is perhaps the most exciting area in all of enterprise technology right now, and it’s evolving at a lightning pace.
Here are four predictions for data science in the new year and how businesses can take advantage of them.
Business people can’t afford to wait for data scientists to provide the analytics they need, so they’re taking matters into their own hands. Python has become more approachable for non-professionals with the availability of preconfigured cloud runtimes and accessible tools like NumPy for numerical data, Prophet for forecasting and H3 for geospatial data. As a result, in 2023, Python use will expand beyond data professionals and into the hands of business analysts and other less technical users.
Novice Python users should not attempt to build their own runtime environments but should opt for any of the modern cloud platforms that provide built-in security and governance. Anaconda offers a popular Python distribution that helps ensure updates and dependencies are managed properly, and Snowflake installs these packages in our cloud-based Python runtime.
There are numerous online resources for non-professionals to get started with Python, including this comprehensive beginner’s guide from RealPython.
4 data science predictions for 2023 by Annie Saunders originally published on TechCrunch
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