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"Stop that!": What does compliance mean for development?
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.
"Whats in a Name?", Data Stories to Impress the Bard
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.
10 DBA Tasks for Azure SQL: Whats Different from On-Prem
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.
300-Level Guide to Career Internals: Planning Your Career
Isn't it awkward when someone asks you, "So, where do you see yourself 5 years from now?" Brent Ozar will share how he analyzed the data job market to build his career path.
5 Mistakes in Cloud Data Migration
We're fortunate in seeing tons of customers migrate to the cloud - this session covers major
500-Level Guide to Career Internals: Building a Brand
If you want to work for yourself, you need to be able to sell yourself. I know, I hate it too - it feels gross when I write it that way. I'm Brent Ozar. You recognize my name, that's why you wanna learn this from me.
A Distributed Availability Groups Primer
A distributed availability group is not your mother's availability group. Want to know more? Attend this session.
A journey through the Tidyverse
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.
Advanced analytics features in Power BI
In this session you’ll learn about some of these advanced analytical features in Power BI, including: the Analytics pane on visuals; the Key Influencers visual and other AI features.
Advanced Azure DevOps With Containers and Pipeline As Code
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 !
Advanced Plan Explorer Usage for Tuning Execution Plans
Users of Plan Explorer often only utilize the basic capabilities to tune execution plans. This session will cover more advanced techniques to get the most out of SentryOne's FREE execution plan analysis tool.
AI For Good: Cognitive Services Vision
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!
AI on Edge, encounter between Data Science and IoT
That session explains how to put AI algorithms on Edge devices, with feedbacks from a computer vision project
Always Encrypted for Beginners
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.
An administrators guide to SQL Server 2019 BDC
Join this session if you are interested in the administration scenarios of the big data clusters, including tooling for monitoring, how to deploy and secure the environment, and to learn about the latest improvements.
An introduction to Azure Synapse Analytics!
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.
Analysis Services DevOps with Tabular Editor
Continuous Integration and Delivery can be a pickle for Analysis Services Tabular Models when using the standard tools. With Azure DevOps, GIT and Tabular Editor, there's a better way...
Analyzing database with XE and Query Store data using R / Py
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.
App Modernization & Migration using migr tools & Azure SQL
In this session, you'll learn about an end-to-end scenario that takes customers through the application migration process, and how that relates to the data migration.
Art of Feature Engineering- For Machine Learning
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.
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