10 Data Science &#038; Big Data Analytics LinkedIn Groups You Should Join
LinkedIn has become the go to place to professionals to seek job, connect with their peers and to share their viewpoints on a particular topic. In this article, we take a look at some of the most popular LinkedIn groups that are dedicated to the field of data science and big data that working professionals, students and those interested in the topic could be a part of 1. Big Data and Analytics Number of members: 353,934 Purpose: The group was founded in 2012 and seen as one of the biggest groups in the platform dedicated exclusively for the discussion, exchanging ideas and providing feedback on matters related to big data and analytics Who can join: To people related to the industry Topics discussed: Artificial intelligence, machine learning, blockchain are some of the topics discussed in the group. Big Data, Analytics, Business Intelligence & Visualization Experts Community Number of members: 251, 776 Purpose: The group aims to bring together stakeholder communities across industry, enterprises, academic, and government sectors with interests in big data and visualization techniques, technologies, and its applications Who can join: Hadoop developers, data scientists, business analysts, statisticians and hackers, CIO, CMO, CDO etc Topics discussed: Hadoop, data warehousing, cloud, unified data architectures, digital marketing, visualization and business intelligence. Business Intelligence Professional (BI, Big Data, Analytics) Number of members: 229,336 Purpose: The group covers the broad area of data analytics and intelligence for businesses. Who can join: Open group Topics discussed: Tools, frameworks, white papers, industry news & best practices in data analytics & intelligence for businesses. 4.Data Mining, Statistics, Big Data, Data Visualization, and Data Science Number of members: 180,572 Purpose:This is a group for data mining and statistical professionals who wish to expand our network of people and share ideas. Who can join: Data mining and statistical professionals Topics Discussed:  Methodological issues are fair game, as well as discussion of software (SAS, R, WEKA, etc), technology (Hadoop, relational databases, etc) conferences, and job postings 5.Big Data, Analytics, IoT (Internet of Things) & Blockchain Number of members: 73,051 Purpose: The group promotes discussion around big data, NoSql and cloud computing etc, among like-minded industry professionals and encourage them to share information, ideas and best practice. Who can join: Industry professionals Topics Discussed: Big data analytics, BI, SAS, big data Hadoop, big data MapReduce, YARN, PIG, Hive, HQL, Oozie, Sqoop, Flume, Kafka, Spark, Big Data NoSQL, HBase, Casandra, MongoDB, HUE, Pentaho, Teradata, BigTable etc Data Scientist Number of members: 63,366 Purpose:  The group aims to solve problems and create products that are valued within  the scientific research community. Who can join: Data Scientists Topics Discussed: Enabling best practice in scientific research, providing an interface between scientific analysis and technology, increasing performance of new applications and data services and decreasing the effort required by researchers in adopting new applications and data services. 7.IBM Big Data and Analytics Number of members:47,704 Purpose: This group is managed by Bruce Weed, IBM’s Programme Director for Enterprise, startups and developers. The group encourages discussions on big data and how IBM’s big data platform can handle customer’s big data needs. Who can join: Customers, business partners, VCs, et al. Topics discussed: IBM Platforms and other products and how they can best handle their database 8.Research Method and Data Science RMDS Number of members: 30,271 Purpose: This LinkedIn forum serve as a platform for those interested in next generation research methods and data science, and related software tools especially open source ones and AI driven ones.  The group also strives to help each other to improve their research quality, predictive accuracy and research efficiency. Who can join: Researchers, analysts and practitioners Topics discussed: research methodology, data science, research flow management, research process standardization, research automation and augmentation, as well as research competency assessment and certification. Data Science and Artificial Intelligence Number of members: 25,338 members Purpose: Data Science and Artificial Intelligence group was started with a vision to be the most active platform for networking, knowledge sharing and educate people who are excited to be a part of this rapidly growing industry. Who can join: Open Group Topics Discussed: Domains, verticals and industries in the space of analytics and big dat 10. Advanced Analytics and Data Science Number of members: 11, 188 Purpose: The group is facilitated by IBM and its mission of the group is to provide the requisite resources for people who are interested in the field to advance their knowledge in the subjects. Who can join: Anyone who want to increase their knowledge in the field of data science and big data can join the group. The existing members include BM Data Science Experience, SPSS Statistics, SPSS Modeler, Cognos Analytics, SAS, R, rstats, Python, Apache Spark, Microsoft, IBM, data warehouse etc. Topics discussed: The group aims to serve as a platform for data science and big data enthusiasts and practitioners to meet people involved with predictive analytics, statistics, machine learning, decision optimization, real-time analytics and big data to have discussions and make connections
LinkedIn has become the go to place to professionals to seek job, connect with their peers and to share their viewpoints on a particular topic. In this article, we take a look at some of the most popular LinkedIn groups that are dedicated to the field of data science and big data that working professionals, […]
In this article, we take a look at some of the most popular LinkedIn groups that are dedicated to the field of data science and big data
["Big Data Analytics", "big data for data science", "linkedin", "Research"]
["data science", "artificial intelligence", "machine learning", "AI", "cloud computing", "big data for data science", "Apache Spark", "RAG", "Big Data Analytics", "Aim", "Research", "analytics", "linkedin", "predictive analytics"]
["AI", "artificial intelligence", "machine learning", "data science", "analytics", "Aim", "RAG", "predictive analytics", "cloud computing", "Apache Spark"]
Akshaya Asokan works as a Technology Journalist at Analytics India Magazine. She has previously worked with IDG Media and The New Indian Express. When not writing, she can be seen either reading or staring at a flower.