The Data Analytics Blog

Our news and views relating to Data Analytics, Big Data, Machine Learning, and the world of Credit.

All Posts

Top 5 LinkedIn Groups To Join On Data Analytics

March 7, 2019 at 12:54 PM

With LinkedIn usage growing by two new members every second, you simply can’t afford to not be on the platform. Founded in 2003, LinkedIn has 590 million users with 260 million of those active every month.

We at Principa are very active on LinkedIn, sharing our blogs and industry news. If you’d like to view our LinkedIn page, click here.

This month, we list our top 5 LinkedIn groups on our favourite topic: data analytics.

Big Data and Analytics

https://www.linkedin.com/groups/4332669/

About this group: Founded in 2012 by Rob Howes, Linkedin Group: Big Data and Analytics have grown to be the largest and most active group of its kind.  With over 300,000 members, it has become the go-to community for all things data.   You will find a wide range of topics including AI, Machine learning, Blockchain, etc.

349 358 members (at time of publishing)

Big Data, Analytics, Business Intelligence & Visualization Experts Community

https://www.linkedin.com/groups/23006/

About this group: A premier community for both existing expert professionals and companies researching the convergence of big data analytics and discovery, Hadoop, data warehousing, cloud, unified data architectures, digital marketing, visualisation and business intelligence.

Who should be a member of this group

  • Hadoop developers, data scientists, business analysts, statisticians and hackers
  • Business leaders and marketers who leverage data to compete and win
  • Enterprise architects, IT, data warehousing, and business intelligence professionals
  • CIO, CMO & CDO of large enterprises.

Currently, this group has more than 200000+ members and growing exponentially.

We hope to bring together stakeholder communities across the industry, enterprises, academic, and government sectors representing all of those with interests in Big Data & Visualization techniques, technologies, and applications. The group needs your input to meet its goals so please join us for the discussion, expert comments, learning's and contribute your ideas and insights.

248 676 members (at time of publishing)

KDnuggets Machine Learning, Data Science, Data Mining, Big Data, AI

https://www.linkedin.com/groups/54257/

About this group: A group for AI, Analytics, Big Data, Data Mining, Data Science, Machine Learning Professionals and Researchers, interested in solving real-world problems - part of KDnuggets network.  You can also follow @kdnuggets on Twitter and subscribe to weekly KDnuggets News Summary email at www.kdnuggets.com/news/subscribe.html

42 431 members (at the time of publishing)

Big Data|Artificial Intelligence|Machine Learning|Predictive Analytics|Data Mining||Data Science

About this group: The purpose of this professional group will be to inform and to discuss different topics and tips from user-to-user and to create a global network of people already using - or interested in using Analytics. Especially the group is going to deal with Big Data, Data Mining, Statistics, Business Analytics, Predictive Analytics, Prescriptive Analytics, Hadoop, Cloud Analytics, Web Analytics and Text Mining.

12,931 members (at the time of publishing)

Business Analytics, Big Data, and Artificial Intelligence

About this group: business analytics, data mining, artificial intelligence, visualisation tools, and predictive modelling, and cloud advanced analytics

199,594 members (at the time of publishing)

collection of data science and machine learning resources

Latest Posts

Africa’s Calling: Contact Centre Conference And Expo

We recently attended the Contact Centre Management Group (CCMG) Contact Centre Conference and Expo, themed Africa's Calling.

How Machine Learning Is Helping Call Centres Improve Their CX

The call centre world, unsurprisingly, ranks as one of the highest adopters of data analytics platforms year on year. This is largely due to the invaluable insights we gain through the analysis of thousands of calls received each day by the typical call centre. With speed being of the essence in making the right decision at the right time for each caller many call centres are turning to machine learning to automate their data analysis and make crucial customer experience decisions within seconds.

AI And The South African Workforce: A Balancing Act

Recently, South Africa was faced with the threat of the biggest banking strike in our country’s history, driven by the job cuts as a result of increasing automation.