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The “top 30” LinkedIn Groups list for analytics, big data, data mining, and data science is a historical directory, not a reliable ranking of the best groups to join today. KDnuggets published it in 2013 using membership counts from April 20 and activity measured from March 11 to April 7. Use the names and figures below as discovery clues, then check each group’s current page, access, rules, and recent conversations before requesting to join.
What the 2013 LinkedIn Groups list can—and cannot—tell you
KDnuggets selected LinkedIn Groups with at least 2,000 members for its 2013 analysis. It counted members as of April 20, 2013, and measured discussions and comments over the four weeks from March 11 through April 7, 2013. Those dates matter: the study does not establish that the groups still exist, remain accessible, or are active now.
The article reported an average of 2.4 discussions and 1.6 comments per week per 1,000 members across the 30 groups studied. These are the study’s historical rates, not current engagement figures. They also show why member count alone is an incomplete way to choose a group: size and participation are different measures.
Which LinkedIn Groups were largest in the 2013 snapshot?
These are the five highest membership counts singled out in KDnuggets’ April 20, 2013 snapshot. They are not current counts or a present-day recommendation.
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| LinkedIn Group | Members reported by KDnuggets | What the name suggests |
|---|---|---|
| Advanced Business Analytics, Data Mining and Predictive Modeling | 76,150 (April 20, 2013) | Business analytics, mining, and predictive modeling |
| Big Data / Analytics / Strategy / FP&A / S&OP | 60,474 (April 20, 2013) | Big data alongside analytics, planning, and finance operations |
| Business Analytics | 39,851 (April 20, 2013) | Business-oriented analytics |
| Big Data and Analytics | 39,560 (April 20, 2013) | Big data and analytics |
| Data Mining, Statistics, Big Data, and Data Visualization | 21,705 (April 20, 2013) | Mining, statistical methods, large datasets, and visualization |
These figures describe membership at one point in 2013. They should not be read as current group sizes or as proof that any group is currently useful.
Which groups had the highest measured activity?
KDnuggets’ most-active list used a combined comments-plus-discussions measure, expressed as events per week per 1,000 members during its March 11–April 7, 2013 observation window.
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| Group | Historical activity rate |
|---|---|
| Data Scientists | 9.64 events per week per 1,000 members |
| KDnuggets Analytics and Data Mining | 8.97 events per week per 1,000 members |
| BIG DATA Professionals | 7.8 events per week per 1,000 members |
| Predictive Analytics Network | 7.68 events per week per 1,000 members |
| Next Gen Market Research | 7.03 events per week per 1,000 members |
The rates are averages from that four-week period, not live readings. KDnuggets’ 2014 update later reported slower overall growth and weaker engagement relative to membership and discussion volume in the period it examined; it noted RDataMining, Data Scientists, KDnuggets, and Big Data and Analytics as active in that 2014 snapshot. Neither historical account substitutes for checking a group now.
How to choose a group for your work
The 2013 directory spans overlapping subjects rather than a single role. Start with what you want to learn or discuss, then compare the actual group pages rather than choosing by an old ranking.
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- Business intelligence and reporting: Look for a current description focused on dashboards, reporting, metrics, or business decision-making.
- Analytics strategy: Check whether the group discusses organizational use of analytics, planning, or business applications relevant to your work.
- Data engineering and big data platforms: Look for conversations about data infrastructure, platforms, and large-scale processing if those are your priorities.
- Data mining and machine learning: Review whether recent posts address methods, modeling, statistics, or applied machine learning at an appropriate level.
Names can be broad or outdated. Confirm that the current description and recent posts match the subject you need, and check the group’s rules and access settings. LinkedIn supports public and private group settings; individual group settings vary.
How to find and join a LinkedIn Group
- Search LinkedIn for the group name or a relevant keyword, such as “business analytics” or “data mining.”
- Open a candidate’s group page and review its description, access information, and rules before deciding whether it fits.
- Use the page’s join option. Depending on the group, you may need to request membership rather than join immediately.
- Wait for a decision if approval is required. Group managers may review requests, and the group controls membership approval.
LinkedIn’s guidance describes Groups as spaces where professionals with shared interests can exchange insights, ask for guidance, and build connections. The details on each group page are the practical guide to that group’s current access and expectations.
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How to tell whether a group is active and worthwhile
Check recent conversations directly on the group page. A large member count or a familiar name does not establish present-day participation. Look for signs that members are responding to one another and that posts have substance, rather than relying on the historical activity rates above.
- Are there recent discussions relevant to your subject?
- Do posts attract substantive replies, or do they receive little meaningful engagement?
- Do the description and rules make expectations clear and fit the way you want to participate?
- Does the group appear accessible to you, and is its moderation approach compatible with your needs?
LinkedIn recommends reviewing a group’s description and rules and contributing relevantly. Avoid irrelevant promotion or repeated cross-posts that do not fit the conversation.
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