|10.00||Registration and Breakfast|
|10.40||Mikko will demonstrate the importance of underlying infrastructure supporting business objectives in accelerating machine learning and creating competitive advantage from data.|
|11.10||Lunch and networking|
|12.30||Using Kafka to integrate DWH and Cloud Based big data systems. |
Data storage has become cheaper and cheaper over time. We're no longer scared of duplicating data many times if it helps optimise our analytics jobs. When migrating from a traditional Data Warehouse to a Big Data system what's involved. For example how do we extract data stored in third normal form in a form usable by BigQuery?
|13.00||Jerome will present Tamr Unify and explain how machine learning can help people across industries to tackle usual problems in MDM, DQ and Data Unification in general.|
|13.30||edge2ai and future road ahead. There has been lot going on in Hadoop sector Hortonworks and Cloudera merger and how tho distributions will eventually merge. Also how HDF/CDF will help Cloudera customers in data integration.|
Matt will be talking about populating graph databases with Kettle using Apache Beam. I will be explaining how easy it is to load data into Neo4j and why we do this. Kettle is used to do it and Kettle running on Apache Beam (using Spark, Flink & DataFlow) and I will do a live demo.
|14.50||Why is Hitachi Vantara seen as a leader in Industrial IoT by Gartner, and how do we leverage Machine Learning in our platform to create manufacturing insights. Kim will walk through use cases and the technologies needed to succeed.|