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 grasp 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.
So why should the cloud be used for data flow? Well, for starts, a key benefit of using the cloud for data flow is the fact that you don't have to worry about setting up or maintaining DMZs. Instead of needing to figure out what devices need to be opened to the internet, and which ones don't, the cloud kind of serves as a natural barrier, I guess you could say. So you don't have to worry about what ports do and do not need to be opened. When deciding how to leverage the cloud for data flow, it's important to consider the usual suspects, like cost, speed, latency, etc. Pulling data into Azure isn't going to incur any costs because its considered ingress, however, pulling that data out later on is going to incur some kind of cost, because it's egress. It's also important to consider latencies and bandwidth for both moving data to Azure and from Azure. With that said, leveraging ExpressRoute and peering ensures data travels through a private connection, which would maintain a steady, and lower, latency than if it was traveling over the public internet. Other benefits to the cloud for data flow processing include the number of services that are available to facilitate the data flow process to begin with. Leveraging functionality as available as platform or as a service, allows you to essentially to hit the ground running.
Simply use the services that you need to design and manage your data flows without any worry about maintenance of the platform or services. The amount of work necessary to get up and running is minimal. To add to that, with such a wide array of services available, you're likely to have access to technologies that you simply wouldn't have access to on-prem. Stuff like machine learning and artificial intelligence would typically fall into this bucket. Leveraging the cloud provides elasticity as well. It allows you to scale almost infinitely if necessary. This isn't something that's easily accomplished on-prem. Cost and time would quickly become barriers to doing so. Instead, the cloud offers the ability to scale up and down as required, while allowing you to pay only for the services and resources that you use. This is especially helpful when dealing with uneven or inconsistent workflows that need to be processed. These benefits, however, will obviously vary on a service by service basis.
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.