In this session you'll learn some of the key data privacy problems facing database developers and DBAs and 10 steps to help your database team build a "defensible position" through development.
Data on its own is useful, but boring. Data in story form makes people sit up and take notice. Learn to craft effective stories and maximise the impact of your data communication.
In this session, we'll cover the 10 most common tasks a DBA needs to learn to manage in Azure SQL as well as they currently manage their On Prem installs.
An introduction to the philosophy of tidy data and the collection of R packages called Tidyverse that help to treat your data appropriately. Including lots of demos from ingesting to cleaning to visualizing your data.
You are a developer and you want to leverage the 'Power' features in Azure DevOps via YAML pipeline as code, then this session is for you !
Curious about Visual Recognition and Object Detection in Azure? Are you wondering what the difference is between the Computer Vision API and the Custom Vision API? Get up Speed with the Vision API in less than an hour!
That session explains how to put AI algorithms on Edge devices, with feedbacks from a computer vision project
Let's learn about what Always Encrypted is, how it works, and the implications for your environment. By the end you will know how to now easily encrypt columns of data and just as importantly how to unencrypt.
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.
DBA and Data scientists should work together! Analyzing data gathered with XE and Query Store data using R or Python for better database insight and discovering hidden patterns.
The most challenging area of machine learning are Data acquisition, Feature extraction, Feature Selection. Almost in all data science project, 80% of time people spend in Data acquisition and Feature engineering.
What is the difference between Artificial Intelligence, Machine Learning and Deep Learning and how can each be used? Join Buck Woody cover simple, clear explanations for these technologies, how they can be applied.
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 Data Factory is a cloud native ETL service built for all data integration needs and skill levels. You can easily construct ETL and ELT processes code free or write your own code.
Data lakes have been around for years yet there is still much hype and hyperbole surrounding their use. This session goes beyond corny puns and broken metaphors and instead provides real-world guidance.
In this session you’ll learn more about Azure data services on Azure Arc
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.
Learn how and where to use Azure Functions in cloud-based ETL processes
Azure Key Vault, Azure Dev Ops and Data Factory how do these Azure Services work perfectly together!
Understand how to create, train and operationalize your data science projects in Azure Machine Learning.
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