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.
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 how Azure supports interactive, exploratory notebooks (e.g. Jupyter) for data processing and experimentation across a range of scales from simple single-computer work up to massively parallel Databricks clusters.
Learn to make better analytic solutions by following current thoughts on data modeling.
Databricks, Lakes & Parquet are a match made in heaven, but explode with extra power when using Delta Lake. This session will dive into the details of how Databricks Delta works and how to make the most of it.
Learn how to take your Azure Databricks Workspace and store all you care about in a git repo, and maybe even have some tests running as part of your release pipelines!
What happens when you combine a cloud orchestration service with a Spark cluster?! The answer is a feature rich, graphical, scalable data flow environment to rival any ETL tech we’ve previously had available in Azure.
Come learn how you can leverage the new and advanced features of Delta Lake on Azure Databricks to easily transform your big data analytics and machine learning workloads
In this session we focus on how Spark implements Machine Learning at Scale with Spark ML.
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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 Databricks has become one of the staples of big data processing. See how to make the most of it by understanding how Spark works under the covers.
This session provides an end-to-end walk through of how to use Azure Synapse for cloud-hosted advanced analytics, based around a real-world predictive maintenance use case.
An opportunity to explore Scala, and why it is truly a “Data Engineers language”. Using Azure Functions, Data Factory, Azure Data Lake Gen2 and Databricks the basics will be explored, followed by real world examples
During this session we will a look at some of the AI approaches adopted by security teams and attackers to, respectively, secure and infiltrate organisations.
Databricks Delta Lake brings new levels of reliability and transformation abilities to big data solutions. Come and learn how you can simplify your ETL and maximise data consistency and resilience, no matter the size
Azure now has two slick, platform-as-a-service spark offerings, but which one should you choose? A separate specialist tools or a one-size-fits-all solution? Join Simon as he compares and contrasts the spark offerings.
Find out how a major UK hotel chain unified their wildly different sources of data to build a supercharged analytics and pricing engine to power their business. Find out how Cosmos and Databricks helped them get to know their customers, how best to retain them, and how best to keep them happy, all while ensuring GDPR compliance and the right to be forgotten.
We will review this new feature of ADFv2, do deep dive to understand the mentioned techniques, compare them to SSIS and/or T-SQL and learn how modelled data flow runs Scala behind the scenes.
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