So you want to build a fast and flexible cloud-based data lake using Azure HDInsight. One early challenge will be to figure out how to keep that lake stocked with the freshest data so you can fish for quality insights. Hand-coded data ingest pipelines are onerous to build and hard to maintain, and traditional ETL tools also perform poorly, especially when faced with changing schemas and real-time streaming use cases. An additional layer of complexity is accounting for hybrid environments mixing on-premise and cloud data sources and storage/compute platforms.
In this webinar product experts from Microsoft and StreamSets will: