Many say data is the new oil, but electricity may be a better analogy. Data powers insights behind critical business decisions but must also be handled safely, properly harnessed, and effectively delivered. Microsoft’s unique combination of Power BI and Azure SQL Data Warehouse (SQL DW) enables customers everywhere to use industry-leading services not only to power their businesses with rich insights, but also store and deliver that data with unmatched efficiency and performance. Join us to learn how Power BI and SQL Data Warehouse empowers your organization to analyze trillions of rows of data and extract instant insights, leveraging Power BI aggregations and composite models to unify data from multiple connections with surprising ease.
Democratizing data empowers customers by enabling more and more users to gain value from data through self-service analytics. Processing raw data for building apps and gaining deeper insights is one of the critical tasks when building your modern data warehouse architecture. In this session, we will show you how to build data pipelines with Spark and your favorite .NET programming language (C#, F#) using both Azure HDInsight and Azure Databricks, and connect them to Azure SQL Data Warehouse for reporting and consumption.
Come to this session to learn how to enable collaboration and solution design for business users and IT specialists to build solutions that enable an organization to harness the power of their big data. This session will enable you to collaborate across business and IT, and show how we can extend intelligence beyond Power BI into Azure Data Services. Once Power BI has landed in an organization, attaching and extending into Azure can be achieved using common use cases and modernization plays.
Gaurav Malhotra joins Scott Hanselman to show how to build a modern data warehouse solution from ingress of structured, unstructured, semi-structured data to code-free data transformation at scale and finally to extracting business insights into your Azure SQL Data Warehouse.Azure Data Factory overviewAzure SQL Data Warehouse overviewAzure Data Factory docsAzure SQL Data Warehouse docsCreate a free accont (Azure)
Having implemented Azure SQL Data Warehouse solutions for dozens of clients, here are the lessons learned we wish we had known several years ago. Learn a great way to make your loads run twice as long. Learn the best ways to make columnstores perform as slowly as molasses in January. Take a visit to the distribution key hall of shame. We review some common mistakes, understand what’s happening under the covers, then show the best practice to fix the problem.
Optimize cost, improve performance, and enhance the security of your DW with automation. This session demonstrates several common automation needs. Learn how to trigger a backup or pause your DW at the end your Azure Data Factory pipeline. Learn how to perform key rotation on SQL login passwords and blob storage keys for Polybase using Azure Automation.
In this session, we review frequent questions from customers about how to best secure their data in Azure SQL Database and Azure SQL Data Warehouse. We share learnings and best practices that customers can use to define a security strategy. For example, we address questions regarding open ports, secure client connections, firewall and VNET rule limitations, limitations on using AAD across services, and more. In the process, we review SQL security features like Vulnerability Assessment, Threat Detection, AAD with conditional access, and Always Encrypted. We also shed light on how we secure the service internally and what we plan to do in the future to protect our customer data against the evolving threat landscape.
In this session, learn about customers building transformational modern data warehouse solutions on Microsoft Azure. Ranging across many industries, come and learn how customers have assembled Azure services such as Azure Data Factory, Azure Databricks, Azure SQL Data Warehouse, Azure Analysis Services, Azure SQL Database and others to deliver amazing results. From cost reduction, to becoming more agile, to aggregating disparate data sources, and handling all of the data emission within their businesses, customers have seen tremendous success migrating to Azure.
In this session you will learn how to develop data pipelines in Azure Data Factory and build a Cloud-based analytical solution adopting modern data warehouse approaches with Azure SQL Data Warehouse and implementing incremental ETL orchestration at scale. With the multiple sources and types of data available in an enterprise today Azure Data factory enables full integration of data and enables direct storage in Azure SQL Data Warehouse for powerful and high-performance query workloads which drive a majority of enterprise applications and business intelligence applications.
Data can be transformative, but it can also be complex to work with. A modern data warehouse on Azure lets you store and analyze all of your data, at any scale, to bring out transformative insights. Find out how.