Microsoft Fabric Data Engineer Certification

Key Takeaways

It definitely sounds like fabric data engineers play a crucial role in supporting their organization's strategic decision-making process. They absolutely do. And to do that, they need to know how to design and manage cuttingedge data solutions that harness the power of [Music] AI. Welcome back to the Azure Essential Show. My name is Aaron Stark and I'm your host. In today's episode, we'll be exploring what it means to be a Microsoft Fabric data engineer and highlight skilling resources to help you on your journey. To help us break it down, I'm joined by my colleague, Heather Shook. Welcome to the show, Heather. Thanks for having me, Erin. Thank you for joining me. So, Heather, can you tell can you start by telling us what fabric is and what it means to be a fabric data engineer? Sure. With Microsoft Fabric, you can give your teams the AI powered tools needed for any data project in a pre-integrated and optimized SAS environment. You can access your entire multicloud data estate from a single data lake that spans the entire organization. Then all this data can flow to everyone in the organization. As a Microsoft Fabric data engineer, you're basically the most advanced users of Fabric with certified expertise in Fabric's advanced workloads. Data engineers can use Fabric to automate data pipelines, transform raw data, and orchestrate complex workflows, ensuring data is available and ready for analysis. Additionally, Fabric supports real time data processing and provides tools for data governance and security, making it easier for you to manage and protect data across the organization. Wow, that's incredible. It definitely sounds like fabric data engineers play a crucial role in supporting their organization strategic decision-making process. They absolutely do. And to do that, they need to know how to design and manage cutting edge data solutions that h harness the power of AI. They also collaborate with roles such as data scientists, analysts, architects, and admins to develop data engineering solutions. I mean, that sounds like a super exciting position to be in. Um, but I'd love to know, how do Fabric's capabilities help data engineers do their job and do it better? Yeah, what's great about Fabric is that its capabilities are always expanding. The platform is incredibly powerful and it helps you design, build, and manage these massive data infrastructures. For example, data engineers use fabric to manage data using lakehouses. And with Fabric's one lake, data engineers can provide a single unified secure data lake for their whole organization, which helps simplify data management. It also helps you use Apache Spark definitions to to submit, batch, and stream jobs to your lakehouse. You can also use notebooks to create and share documents using various programming languages like Python. Okay, that's super interesting. It sounds like data engineers using Fabric are uniquely positioned to make important contributions to the organizations. And for our viewers um that might be super interested in this, what sort of skills and knowledge do these data engineers need to be successful? Glad you asked. Data engineers should be well-versed in a variety of different tools and technologies that build resilient, scalable, and secure data systems. But specifically, data engineers need a deep knowledge in things like data loading patterns, modern data architectures, and orchestration processes. As you know, the world of data moves fast. So, data engineers need to be continually learning and evolving, right? Absolutely. Processing continuous data streams has become essential for modern data analytics solutions. So, today's data engineers need to know real-time data analytics and it's also important to have expertise in lakehouse environments as well as implementing continuous integration and continuous deployments across the development life cycle. I mean, from the data infrastructure from CI to CD, it definitely sounds like this is a lot to stay on top of. But I'm curious, what does Microsoft offer to help boost the careers of data engineers or anyone interested in becoming a data engineer? That is such a great question. I'm so glad you asked. The first thing I would highlight is the DP700 fabric data engineer certification. This is a role-based industry recognized credential that not only gives you a boost on your resume, but it also helps differentiate you as someone on the cutting edge in the field of data and AI. Who wouldn't want that, right? You can also combine this with the DP600 certification for the fabric analytics engineer associate role. This certification is analytics focused and helps you round out your skill set. It emphasizes making sure the data is usable for the business versus connecting other data sources. Ah, okay. Thank you so much for the clarification. And now I'd love to talk about some ways that data engineers can actually prepare for a certification. Yeah, we definitely don't want you to feel like you're on your own here. So, we've got plenty of resources to help you. It starts with an official plan on learn and helps that helps you prepare for your DP700 certification exam. It's a curated skilling resource that aligns directly with the exam and offers milestone-based learning to get you on the path to subject matter expertise. It covers the core features and capabilities of lakehouses and Microsoft fabric Apache Spark data frames as well as how to use real time intelligence to ingest, query, and process streams of data. And the best part about this plan is that it nudges you via email after you've completed key milestones. So it keeps you moving towards specific learning outcomes and ensures that you're prepared for the exam. Definitely. And I know some of our other guests have also utilized plans which is always a great single resource for an end toend skilling journey. Um but I'd love to know a little bit more or any specifics around u additional skilling resources for data engineers that are specifically interested in fabric. Absolutely. There's also a learning path that helps you implement operational databases in fabric. This learning path guides you through the process of creating and managing SQL databases within a fabric environment. So it essentially introduces topics like data modeling, query optimization, and performance tuning specifically to fabric SQL capabilities. You'll also learn how to provision a SQL database, configure security settings, and perform essential database operations. Great. And that sounds like a ton to actually get you prepared. And we also know that the ability to work with and deploy AI for data engineers is going to be essential. Do we have any resources that might be specifically geared to AI? We absolutely do. We have an official plan on learn that will help you make your data AI ready. It's a free self-paced and ondemand plan that teaches you how to implement large-scale data engineering and explore warehouse solutions. You'll learn how to ingest data through shortcuts, mirroring pipelines, and data flows. You'll learn how to transform data using data flows, procedures, and notebooks. And of course, you're also taught how to store processed data in a lakehouse and a data warehouse so it can be easily retrieved and ready for AI. Wow, that is an incredible amount of resources and this has been such a great conversation about skilling and fabric data engineers. Um, these are some great ways for data engineers to stay competitive in a fast-paced industry. Thank you again so much for joining us today, Heather. And thank you so much for sharing all of these resources for us. Thanks, Erin. It's been fun. You can find links for all the resources and learning plans that we covered in today's episode in the description below. Don't forget to leave your feedback in the comments. Let us know if you've started any of these plans or how your organization might benefit from Fabric. Also, make sure that you give our show a like and don't forget to subscribe so you don't miss any new episodes that drop. Thanks again for watching and we'll see you on the next episode of the Azure Simple Show. [Music]