|Date:||Aug 8, 2016|
34 Shaddock Street, Eden Terrace, Auckland
|Time:||17:30 - 18:30|
ABOUT THE EVENT
The New Zealand Big Data and Business Intelligence Meetup has been formed to encourage collaboration and innovation in Data technology in New Zealand. It is sponsored by Callaghan Innovation and ATEED.
The group explores interesting use cases, in different industries and shares tools, techniques and good ideas that are available for big data and BI projects. The group is for people who are interested in data storage, aggregation, transformation, search, analysis, visualisation and decision support. We will investigate and discuss cross-platform, cross-language technologies such as NoSQL, SQL, Hadoop, Cassandra, Couchbase, Pentaho.
During this event Colman Madden, Senior Data Engineer at MapR, and Justin Bock , Regional Sales Director at MapR, will be delivering their talk and demo "Introduction and Demo of the MapR Converged Data Platform". Join this event here: http://www.meetup.com/NZ-Big-Data/events/233049368/
- Spark SQL & Machine Learning - A Practical Demonstration by Craig Warman - Solutions Engineer/Architect at MapR
Colman and Justin will demonstrate how quickly real-time data pipelines can be built to process, store, index and visualize data in real time. This will involve MapR Streams (Kafka API) with Kibana, Elasticsearch and also Streamsets. They will also demonstrate how Apache Zepellin and Apache Drill can be used to query the persisted data.
About MapR Platform
The MapR Converged Data Platform is the industry’s only platform to integrate the enormous power of Hadoop and Spark with global event streaming, real-time database capabilities, and enterprise storage. The platform supports a full set of open API’s (Hadoop, Hbase, Kafka) and also a large number of Apache open source projects including Hive, Drill, Spark, Mahout, and Zookeeper etc.
Streams is a global publish-subscribe event streaming system for big data. It connects data producers and consumers worldwide in real time, with unlimited scale. Publishers (data producers) write data to one or more topics.
Subscribers (data consumers) to the topic can read the data instantaneously, anywhere across the globe.
Streams is unique for two reasons. First, it is the first big data-scale streaming system to be built into a converged data platform. Next, it is the only big data streaming system to support global event replication at Internet-of-Things (IoT) scale and reliability, providing failover endpoints between up to thousands of distributed clusters.
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