Cloud data and AI services training roundup August 2018
To help you stay up to date on online training opportunities, we’re releasing a monthly list of the latest free Data and Artificial Intelligence (AI) sessions in one convenient post.
SQL Server
Build modern applications using the language of your choice, on-premises and in the cloud, now on Windows, Linux, and Docker containers.
- Prepare for Windows Server 2008 and SQL Server 2008 End of Support
Support for SQL Server 2008/ 2008 R2 and Windows Server 2008 will end in July 2019 and January 2020, respectively, which means you’ll no longer receive security patches for these versions. When you join this session, you’ll learn how to migrate your applications and data, avoid business disruptions, and adopt the most current security technologies. You will also receive guidance for your migration and find resources to help you move quickly.
Azure Database services for PostgreSQL and MySQL
Azure Database Services for PostgreSQL and MySQL provide fully managed, enterprise-ready community PostgreSQL/MySQL database as a service. These community editions help you easily lift and shift to the cloud, using languages and frameworks of your choice. On top of that, you get built-in high availability and capability to scale in seconds, helping you easily adjust to changes in customer demands.
- How Open Source Database engines help you migrate to Azure
Learn how to take advantage of fully managed, enterprise-ready PostgreSQL and MySQL community database engines. Join us as we cover how to use Azure Database Migration Service and what incentives are in place to help you in your migration journey.
Azure Cosmos DB
Azure Cosmos DB offers the first globally distributed, multi-model database service for building planet-scale apps.
- Controlling your application experience with Azure Cosmos DB’s consistency models
The ability to control your application experience by changing your consistency model has been lacking—until now. Azure Cosmos DB offers five well-defined and preconfigured consistency models, helping you navigate the tradeoffs between data consistency and app availability. In this session, learn the key differences between the five consistency models, which applications are best suited for each model and how to configure the models to ensure high performance.
Big Data and analytics
Deliver better experiences and make better decisions by analyzing massive amounts of data in real time. Get the insight you need to deliver intelligent actions that improve customer engagement, increase revenue, and lower costs.
- Making R-based analytics easier and more scalable
R is an increasingly popular programming language for running predictive analytics workloads. If you are looking to scale out R-based advanced analytics to big data, Azure Databricks starts in seconds, integrates with RStudio, and automatically executes R workloads at unprecedented scale across single or multiple nodes. Join us to see how to get the ideal dataset for your needs and a detailed demonstration of the entire solution.
