What we're about
This meetup aims to develop best practices for data mining and practical analytics that get results. Our focus will be on the practical areas around:
• understanding analytics and "big data"
• ingesting, formatting, validating, and exploring data
• designing behavior-changing metrics
• developing and designing appropriate data architectures
• proven strategies, technologies, stacks, and pipelines
• when to build, when to buy, what to buy, why buy
We have no affiliations with data product / platform vendors. If you would like to contribute to our budding Meetup, please reach out!
Areas: data mining, analytics, big data, machine learning, data science, business intelligence, olap oltp, recommendation systems, predictive analytics, design patterns, message queues, actor pattern, publisher subscriber pattern, hash joins, leading indicators, classification, batch processing
Technologies: hadoop, hdfs, hive, pig, spark, sql, kmine, r, scikit-learn, drill, prestodb, flume, protodata, nosql, druid, rethinkdb, kafka