Designing Data Flows in Azure
Data Flow Basics
Designing a Data Flow Solution
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This Designing Data Flows in Azure course will enable you to implement the best practices for data flows in your own team. Starting from the basics, you will learn how data flows work from beginning to end. Though we do recommend an idea of what data flows are and how they are used, this course contains some demonstration lectures to really make sure you have got to grips with the concept. By better understanding the key components available in Azure to design and deploy efficient data flows, you will be allowing your organization to reap the benefits.
This course is made up of 19 comprehensive lectures including an overview, demonstrations, and a conclusion.
- Review the features, concepts, and requirements that are necessary for designing data flows
- Learn the basic principles of data flows and common data flow scenarios
- Understand how to implement data flows within Microsoft Azure
- IT professionals who are interested in obtaining an Azure certification
- Those looking to implement data flows within their organizations
- A basic understanding of data flows and their uses
Related Training Content
For more training content related to this course, visit our dedicated MS Azure Content Training Library.
In this brief lecture, I want to touch on what database services are available in Azure. Getting back to our previous data flow example of the casino, the database service is the source of information. Player info from the floor's slot machines is continuously written to the backend database. In turn, the data from the database is then fed in as the source for the casino's overall data flow. That said, in other scenarios, the database service can serve as some intermediary step in the data flow process or it can even serve as a data mart. There are many different database services available in Azure. They are available as both platform as a service offerings, as well as database as a service offerings. For example, Azure offers services such as Azure SQL Database and Cosmos DB. Because Cosmos DB is a NoSQL implementation, it's a good fit for data such as documents and graphs. Conversely, because Azure SQL Database is a more traditional relational database, it's better suited for relational data. There are also several infrastructure as a service options available as well. You can simply run a database instance within an infrastructure as a service virtual machine, if platform as a service isn't your thing for some reason. So when designing a data flow, you may find yourself splitting between or among multiple models or even platforms due to the data that needs to be processed.
Tom is a 25+ year veteran of the IT industry, having worked in environments as large as 40k seats and as small as 50 seats. Throughout the course of a long an interesting career, he has built an in-depth skillset that spans numerous IT disciplines. Tom has designed and architected small, large, and global IT solutions.
In addition to the Cloud Platform and Infrastructure MCSE certification, Tom also carries several other Microsoft certifications. His ability to see things from a strategic perspective allows Tom to architect solutions that closely align with business needs.
In his spare time, Tom enjoys camping, fishing, and playing poker.