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Azure AI, Power new possibilities for every organization Lindsey Allen
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.
Building Modern Data Warehouse with Azure Synapse Analytics! Mahesh Balija
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-Our new buddy for Data Governance Oliver Engels
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
Data Exploration & Experimentation with Notebooks in Azure Ian Griffiths
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.
Data Modeling Trends for Analytics Ike Ellis
Learn to make better analytic solutions by following current thoughts on data modeling.
The video is not available to view online.
Databricks, Delta Lake and You Simon Whiteley
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.
DevOps your Databricks Workspace Simon Sabin
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!
The video is not available to view online.
ETL in Azure Made Easy with Data Factory Data Flows Paul Andrew
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.
How Delta Lake with Azure Databricks can accelerate your big data workloads Bhanu Prakash
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
Machine Learning in Azure Databricks Terry McCann
In this session we focus on how Spark implements Machine Learning at Scale with Spark ML.
Microsoft certifications for the Data & AI professional Sandra Marin
Are you looking to take your career to the next step? Microsoft Certifications help validate knowledge and ability required to perform current and future industry job-roles in a modern digital business. Our certification
Navigating the Bewildering Array of Data Services in Azure Ian Griffiths
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.
Performance Optimization with Azure Databricks Richard Conway
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.
Predictive Maintenance with Azure Synapse James Broome
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.
Scala for Big Data the Big Picture Anna-Maria Wykes
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
Securing the Future with AI Darshna Shah
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.
Simplify your ETL with Databricks Delta Lake Piotr Mucha
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
The Azure Spark Showdown - Databricks VS Synapse Analytics Simon Whiteley
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.
Azure Cosmos DB and Databricks for CRM Optimization Simon Hayward
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.
Azure Data Factory v2 with Data Flows capabilities Kamil Nowinski
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.
Azure Databricks for ML on Big Data workloads Mahesh Balija
Azure Databricks support both Classic and Deep Learning ML Algorithms to analyse Large DataSets at scale. The Integrated Notebook experience gives the Data Scientists and Data Engineers to do exploratory Data Analysis, also feels like native to Jupyter notebook users. In this session we will extract intelligence from Higgs Dataset (Particle Physics) by running Classic and Deep Learning models using Azure Databricks. We will also peek into AMl service's integration with Azure Databricks for managing the end-to-end machine learning lifecycle.
The video is not available to view online.
Data Integration with Azure Cosmos DB, Data Factory and Databricks Neil M
Azure offers a vast comprehensive data estate! While this is great for enabling users to pick the right tools for the right job - this has also increased the surface area for understanding how to integrate a vast number of components. In this session, we will show off the plug and play nature of Azure products by showcasing you can write to Azure Cosmos DB with a data pipeline moving data from multiple sources powered by Azure Data Factory and Databricks.
ETL with Azure Databricks, The Complete Introduction Andre Kamman
We’ll take a look at how to approach making an Azure Databricks based ETL solution from start to finish. Along the way it will become clear how Azure Databricks works and we will use our SSIS knowledge to see if it can handle common use-cases
The video is not available to view online.
Modern Data Warehousing with SQL DW and Databricks Philip Beaumont
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.
The video is not available to view online.
Python Pipeline Primer: Data Engineering with DataBricks Simon Whiteley
Azure DataBricks is a PaaS offering of Apache Spark, which allows for blazing fast data processing! How can data engineers harness the in-memory processing power? Azure DataBricks can be your data ingestion, transformation and curation tool of choice
The video is not available to view online.
The Maths behind Machine Learning Matt Willis
With a strong focus on the algorithms used in Machine Learning, we will explore the maths involved to gain a deeper understanding. Using practical examples, with Databricks to consume a dataset and Python scripts to execute the models.
The video is not available to view online.
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