Azure Synapse Analytics combines the power of Data Lakes with Data Warehouses, empowering the organizations to build Big Data, Advanced Analytics and Business Intelligence in one single platform.
AI and data is at the center of the digital feedback loops. We have invested in a comprehensive portfolio of AI tools, infrastructure and services. Come to this session to get an update of Azure AI with demos.
In this action-packed demo full session, we will be showing you how to combine Azure DW and Power BI to get optimal performance for running your day to day reports.
In this session we explore Azure Synapse Analytics, we will dive into this limitless analytics service and explore how it brings together enterprise data warehousing and Big Data analytics.
Come learn how Azure Synapse brings together big data and data warehousing through new technology and a unified development experience
Together Power BI and Azure Synapse Analytics can handle huge datasets. This session details how the composite model and aggregation capabilities of Power BI can be used to fully exploit the scale provided by Synapse.
Azure Synapse Analytics combines the power of Data Lakes with Data Warehouses, empowering the organizations to build Big Data, Advanced Analytics and Business Intelligence in one single platform.
Common Data Model as the foundation of Power BI Dataflows and as part of the Open Data Initiative with SAP and Adobe, seems to be a pretty good move from Microsoft. We want to take a closer look to this approach
Learn to make better analytic solutions by following current thoughts on data modeling.
Delivering enterprise BI with Power BI Premium tabular cubes, Azure Databricks ETL and Delta Lake for transaction integrity
Azure Synapse now provides a Query-as-a-Service capability to enable serverless exploration over your data lake with no infrastructure or clusters - all you need to know is T-SQL.
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This session will dive into how to successfully migrate to Azure Synapse, all the way from code conversion to enterprise grade developer tooling, with real customer examples for product and migration experts.
Azure's breadth of products can make technology selection a challenge. Learn how to make pragmatic and informed choices that meet your application's data transformation, processing and storage requirements.
Azure Data Share enables organizations to simply and safely share data with their customers and partners. Watch a live demo, hear how customers are using the service and how we're thinking about governed data sharing.
The session is for everyone who knows the data warehousing concept and wants to broad theirs horizons with modern capabilities of processing the data at scale.
A technical overview of Azure SQL Data Warehouse Gen 2. SQL Data Warehouse is a cloud-based Enterprise Data Warehouse (EDW) that leverages Massively Parallel Processing (MPP) to quickly run complex queries across petabytes of data.
Using Azure DevOps and Azure RM templates to created isolated environments for testing PaaS solutions.
In this session we will learn which processes are required to build a real-time analytical model along with batch-based workloads, which are the foundation of a Lambda architecture.
SQL Data Warehouse is a cloud-based Enterprise Data Warehouse (EDW) that leverages Massively Parallel Processing (MPP) to quickly run complex queries across petabytes of data. Azure Databricks is a fast, easy and collaborative Apache Spark-based analytics service that can be used for big data analytics and artificial intelligence (AI) solutions. This session will cover the architecture patterns for using the two in synergy.
This quick vendor session demonstrates the spectrum of SentryOne's best-of-breed products for the Microsoft Data Platform, from Task Factory, to Plan Explorer, to DOC xPress, to the SentryOne monitoring platform, and beyond.
In this talk we will discuss best practices around how to design and maintain an Azure SQL Data Warehouse for best throughput and query performance.
We will showcase the latest feature of SSIS 2017 such as connectors for Azure Data Lake Store (ADLS), Azure SQL Data Warehouse (SQL DW), SSIS Scale-Out at package level for the box product as well as the SSIS package execution on Azure Data Factory
Learn about the new compute optimized performance tier in SQL Data Warehouse and how to maximize your performance through improved table design and columnstore optimization.
In this session we will discuss about the Azure SQLDW and how we can use it to help on our day to day.
This session covers the more advanced aspects of development for Azure SQL Data Warehouse. Areas such as data movement, workload concurrency and resource management will all be covered during this intense 60 minute session.
Data Warehouses are changing. This session will run through the architecture of the modern warehouse, from structured/unstructured Azure Data Lakes to platform as a service Azure Data Warehouse and bringing the two together.
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