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.
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.
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 group is not your mother's availability group. Want to know more? Attend this session.
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 !
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.
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.
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.
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...
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.
In this session you’ll learn more about Azure data services on Azure Arc
Come join us in the intelligent database world that started with SQL Server 2017 and takes a leap forward with the upcoming SQL Server 2019 and Azure SQL DB.
In this demo intensive session I will show you how to tackle the most challenging tasks with Extended Events without writing a single line of code.
Learn what the Database Experimentation Advisor is and how you can start using it to baseline performance from a target and source server when new changes are introduced.
If AI is on the cards in your business you might need to make a recommendation as to whether your company should Buy or Build. Come to this session to work out the moving parts to turn "It Depends!" into an answer.