r/analytics for B2B sellers
285,088 members · rules and posts checked 17 October 2026
r/analytics is an analytics community with 285,088 members. Sellers can't post to promote a product or service, and advertising is discouraged.
People here often ask for learning resources, datasets, SQL practice platforms, industry news sources, networking opportunities and data-modeling tools. They also ask for advice on analytics work and AI readiness.
Self-promotion: not allowed
Self-promotion and advertising are not allowed. The rules specifically discourage promoting tools or solutions and ask members to focus on techniques and knowledge-sharing instead.
1Be Nice
Be respectful and professional.
2Blog Spam
Do not promote your blog by linking to it.
3Career Advice & Interview Assistance
Keep career advice and interview-help posts in the stickied thread.
4Advertising & Promotion
Do not advertise or promote products; discuss techniques instead of tools.
Summarised from the community's posted rules on 17 October 2026. Moderators change rules; read the current rules before you post.
What buyers ask for here
Sample requests from public posts, paraphrased and anonymised, found 17 October 2026.
- “Looking for public marketing datasets with related tables to practice joins and detect duplicated spend.”
- “Seeking recommendations for companies or services that can perform a data-readiness assessment before an AI initiative.”
- “Looking for a free platform to practice advanced SQL and build projects for interview preparation.”
- “Seeking networking events or tech conferences to attend during an upcoming visit.”
- “Looking for data-modeling tools to control warehouse costs and support BI and AI-agent use cases.”
- “Looking for useful industry news sources, blogs, newsletters, or people to follow in analytics.”
- “Looking for sources of datasets for analytics and data-science practice projects.”
Of 120 recent posts we checked, 7% read as someone looking to buy or hire. How we collect this
Who it suits
Good for
- Analytics training and education
- Data infrastructure and governance tools
- Business intelligence and reporting software
- Analytics consulting and advisory services
Less useful for
- General consumer products
- Direct-response advertisers
- Aggressive lead-generation or self-promotional services
How to take part without getting removed
- Be respectful and professional in all discussions.
- Do not advertise or promote products or services.
- Share techniques, knowledge and practical guidance instead of pitching tools.
- Do not post links to promote your blog.
- Keep career advice and interview help in the stickied thread when relevant.
What a good reply looks like here
A good reply answers the question directly and shares useful knowledge without promoting a product or service.
Sample reply: For practicing joins and finding duplicated spend, look for public marketing datasets with several related tables rather than single flat files. Datasets with campaign, channel, spend and conversion tables work well for join practice and data-quality checks. You can also combine a few public datasets into a simple warehouse model, which gives you realistic exercises for duplicate detection and reconciliation.
When to skip r/analytics
This community is a poor fit for lead generation, product promotion or selling services directly. It's more useful for learning, sharing expertise and seeing what analytics practitioners ask about than for outreach.
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