Session Details

Designing Modern Data and Analytics Solutions in Azure

Full Day
Design
Business Intelligence and Data Warehousing
BI/Analytics Practitioner, DBA
200
This full-day session will focus on principles and practices for architecting modern analytics/BI/DW systems in Azure. We will discuss Azure fundamentals, implementation strategies, key decision points, and lessons learned from customer projects. Cloud design patterns will be explored, including cloud-specific concerns and considerations, as well as key differences from traditional on-premises deployments. Reference architectures will be presented which address scenarios such as real-time data ingestion vs. batch loads, data virtualization vs. data integration, schema on read vs. schema on write, SQL on Hadoop, high data volumes, varying file formats, enabling data science, and facilitating self-service BI. After considering various reference architectures, we will proceed with building an end-to-end solution for one reference architecture based on requirements presented to the audience. Approximately 30% of the day will be hands-on labs, 50% presentation, and 20% open discussion and questions. Specific technologies discussed will include: Azure SQL Database, Azure SQL Data Warehouse, Azure Data Lake Store, Azure Data Lake Analytics, U-SQL, Azure Storage, Azure Data Factory, Azure Databricks, Spark, Hive, HDInsight, Azure Analysis Services, PolyBase, Elastic Queries, Azure Event Hub, Azure Stream Analytics, Azure Data Catalog, Machine Learning Services, Azure Machine Learning, Azure Cognitive Services, Power BI, BIML, ARM templates, PowerShell, and Azure Virtual Machines. Attendees of this session will gain a broad understanding of the fundamentals for designing data solutions in Azure, techniques for navigating the wide variety of platform choices in Azure, and suggestions for developing sound architectural systems.
Familiarity with developing BI/analytics systems will be very helpful, but is not required. No Azure experience is required.

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