5 Data Analytics Forums To Follow and Why
March 31, 2022
COVID-19 has rocked the business world in many ways, one of them being in-person events; conventions, conferences, and other opportunities for idea sharing are canceled for the remainder of 2020. Luckily, the internet is home to some informative and dynamic forums that can provide professionals with valuable professional development and industry connections.
To get our data-loving customers started, we’ve identified five of the best forums for those working with (or are interested in) data analysis and business intelligence.
We rank Reddit’s Data Science forum first because it’s highly active and sees a ton of responses, a benefit of living within one of the most visit websites in the world. The downside? You may have to do some sifting to find more specific information, as topics range widely. For beginners exploring their interest in data science, there are plenty of posts asking for definitions and explanations, as well as professional guidance (“Should I get a Master’s Degree in Data Science?”). For the more advanced, participants can find freely shared algorithms, tips on more efficient setups, and creative project ideas.
May we also suggest: Github’s Data Analytics repository is useful for data scientists and those with more in-depth technical knowledge of data analytics. The posts are heavy on coding-related topics–Python in particular. Visiting this page will give you access to course repositories, pre-built spreadsheets for independent use, and the occasional troubleshooting post.
Whereas someone could spend hours surfing through Reddit’s Data Science forum, those who need a quick answer to a straightforward question might like Analytics Vidhya’s Discussions forum, where threads close out quickly. Analytics Vidhya offers data science courses, so the forum’s topics are suitable for both beginners and those who want to continue their learning. Even for the average person, some of the posts are a unique look at how people are using data analytics to solve problems, like this person building an algorithm to assess hate speech on Facebook. The downside is that while post views are in the hundreds, each one averages only two replies, so you won’t get heavy input. Discussion topics have included best practices for creating data sets, regression analysis, and open-source tools.
May we also suggest: Quora can be an unmatched interactive resource for life advice, and that holds for many things data science. From breaking down the pros and cons of related academic degrees and certifications to deeper Google Analytics dives, this site is a priceless Q&A hub for things like business intelligence, mobile user analytics, computer network know-how, statistics, Artificial Intelligence, and more.
Facebook’s Data Science Group
With almost 120,000 members, Facebook’s Data Science Group sees activity every day.
May we also suggest: Don’t forget LinkedIn, which is an internet forum in itself if you join active groups like Machine Learning and Data Science or Big Data and Analytics. More recent discussions include an invitation to a free online data science boot camp, feedback on a deep learning article, and an overview of data visualization for COVID-19. Facebook also has a (private) Big Data & Data Analytics Group with more than 20,000 members. Industry-specific professionals should check out pages like Data Analysis for Digital Marketing and Analytics / Machine Learning / Data Mining (private). There’s also this roundup of data analytics groups on LinkedIn, which are more focused on business analytics.
Data Science Central
Data Science Central’s online groups rank consistently in forum recommendations– and perhaps that’s because this set of 16 groups offers easy access to scientists around the world. The website’s discussion boards cover data science apprenticeships, a wealth of analytics-related resources, and topic-specific posts (e.g. IoT or bioinformatics).
Dataquest Community Dashboard
Dataquest’s interactive forum is divided into three categories: Q&A, Social, and Knowledge Base. The Q&A section is useful for posting technical questions; the Social section hosts discussions around ideas, concerns, and recent developments; and the Knowledge Base portion is for members of the company’s online learning community.
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