Azure Synapse Analytics - Part III - Serverless SQL Pool

Azure Synapse Serverless SQL Pool facilitates data exploration, transformations and data warehousing with multiple functionalities, allowing us to work with it using SQL. This video discusses how it works, what we can do and demos on use cases. This is the content:

• Introduction to Serverless SQL Pool
• How useful it is
• Is it same as Dedicated SQL Pool?
• Demo
• Data exploration
• Data transformation
• Making a logical data warehouse and accessing it using Power BI

Read more at:
Serverless SQL Pool Architecture Serverless SQL Pool - Microsoft Learn

Azure Synapse Analytics - Part II - Hypersapce

 *** This is the session I have done for Sri Lanka Data Community – Feb 2022 episode. This does not contain the entire event.

With modern data solutions, where we see data warehousing and big data, analytics are not limited to columnar based queries, highly selective queries are part of the trend now. Here is the way of optimizing such queries with Hyperspace: An indexing subsystem for Apache Spark. Read more at: https://docs.microsoft.com/en-us/azure/synapse-analytics/spark/apache-spark-performance-hyperspace?pivots=programming-language-csharp/?WT.mc_id=DP-MVP-33296

https://github.com/microsoft/hyperspace/?WT.mc_id=DP-MVP-33296

This talks about - What is Hyperspace and how it helps us to add indexes - How to see indexes, what changes it makes to the data lake - How to check whether indexes are used for queries - How to compare indexed query and non-indexed query with given APIs If you have any questions, please add to the comment section.

Azure Synapse Analytics - Part I

 This video speaks about the latest in data warehousing and big data analytics: Azure Synapse Analytics. This is the first part of it and it explains;

- The way we have been creating on-premise data solutions

- The way we have been creating data solutions in Azure before Azure Synapse Analytics

- How we can create data solutions in Azure using Azure Synapse Analytics

- Quick demo on creating the workspace, SQL Pool, Spark cluster and accessing and processing data