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.
Throughout this course, we're going to talk about the basics of data flow, starting with the fundamentals. We'll talk a bit about how you can provide data flow solutions using Microsoft Azure services. We're going to discuss a few reference architectures as well, so we can kind of pull everything together. We'll also cover some common data flow scenarios, so you can better understand the requirements, the technologies, and the core data flow pipeline. These basic concepts are important because businesses need to know where they are performing well and where they are performing poorly. We need to ask hard questions about where the business is and where it's headed. Such answers can be pulled from the data that's collected by the business itself.
There may even be cases where additional questions about the business might be asked in the future. As such, it's critical to keep raw data around for some time, so any future questions can be answered. The concept of data flow encompasses the initial ingestion of data, any required transformations, storage of the data and then, ultimately, analysis of the data. Data flow is essentially about what needs to happen with the data in order to meet business requirements and how it can be used to answer questions about the business. As such, it's important to get this right. Without the right data flow, a business may not be able to find answers that it needs today, let alone answers it might need in the future.
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.