Datascape Podcast Episode 40 – What is Azure Analytics Synapse?
If you were a preexisting SQL Data Warehouse customer, then you’re technically now a Synapse customer using an SQL pool. In this episode, Chris sits down with Warner to discuss Azure’s SQL DW rebranding to Azure Synapse Analytics. The rebranding is not just a question of changing names though but involves incorporating SQL DW into Synapse while additionally offering a host of new functionality intended to provide a full end-to-end analytics development experience. One can now go into their Synapse Analytics workspace and have everything they need to do to be able to develop or consume the analytics.
We talk about some of these new features such as the addition of big data pools, on-demand computing, and the integrated catalog. Our conversation covers how data is ingested and we hear about how Spark integrates with classic SQL style searching, meaning you will be able to query back and forth through the two sets of results transparently. Warner also gets into the shelving of USQL in the Gen2 framework, how data gets moved from on-prem into the Synapse framework, and integration into ETL providers. You’ll also learn about the relationship between SQL DW accessibility and how Microsoft is dealing with security concerns this raises. We talk about data masking, key methods, shrinking DVA, and execution plan types.
Finally, Warner gets into how somebody might start learning Synapse and lends insight into paid models versus free resources. For everything you need to know about Azure Synapse Analytics and more make sure you join us today!
Key Points From This Episode:
• Modifications in the Azure Synapse Analytics rebranding; doing more than Azure SQL DW.
• SQL Pools, the new SQL Data Warehouse, and their ability to have multiple versions running.
• New features in Synapse Analytics which make it a fully integrated environment.
• How data is ingested using Data Lake storage or SQL Data Warehouse depending on need.
• The role Spark plays in the Synapse environment: one of two integrated styles of analytics.
• A shelving of Azure Data Lake Gen1’s USQL; integrating Synapse with TSQL using SQL DW.
• Moving data from on-prem into Synapse for analytics and processing depending on scale.
• How big ETL players all have full integration with the big cloud providers, Azure included.
• The ability of SQL DW to connect to third party software: it’s not locked down.
• How despite accessibility, Synapse tries to provide regular SQL server-level security.
• Whether your own key methods have superior security capabilities than Microsoft keys.
• Dynamic data masking and role level security functionality provided by SQL Pools.
• How data masking works by masking functional data when pushed to the client.
• Low administrative tasks required in Synapse; how DVA tasks are shrinking.
• The difference between specific versus distributed execution plans.
• How performance and security are two of the main administrative concerns in Synapse.
• Limitations to the purely SQL Server DVA model and being really good at it.
• A warning to be careful of the DW1000 portal’s costs when learning Synapse.
• Recommendations for free resources for learning Synapse: Microsoft Ignite 2019 talks, etc.
• Timeframes for the release of different new previews of features of Azure.
• And much more!
Links Mentioned in Today’s Episode:
Microsoft Ignite
Azure Synapse Analytics
Google BigQuery
Warner Chaves on LinkedIn
Warner Chaves on Twitter
Datascapes SQL DW Episode 20
