In today's blog, we will continue to explore Microsoft's new certification portfolio. Our focus will be on the Data & AI training stream.
There has been a tremendous amount of innovation around Data & AI services in Azure. The corresponding Microsoft certifications are thus evolving to keep up with demand and changes to underlying technologies. In this post, we would review the Data & AI certification portfolio and see how you can benefit from it!
First, let's sync up with some very recent developments in this certification area. Within the past few weeks, Microsoft made 2 important announcements:
- All MCSA, MCSD, and MCSE certifications are being retired. This also impacts all corresponding MCP exams.
- Two new data-related certifications are arriving in early April.
The first announcement was expected by many of us in the industry. Recent learning investments from Microsoft have almost exclusively all been in the role-based certification space. Thus it makes sense to take the legacy product-based certification streams completely off the market. Otherwise there would simply be too much choice, duplication/overlap and possible confusion.
The following data-related certifications are impacted by this decision:
- MCSA: BI Reporting
- MCSA: SQL 2016 BI Development
- MCSA: SQL 2016 Database Admin
- MCSA: SQL 2016 Database Dev
- MCSA: SQL Server 2012/2014
- MCSE: Data Management & Analytics
And these are the impacted data-related exams:
- 70-417: Upgrading Your Skills to MCSA Windows Server 2012
- 70-461: Querying Microsoft SQL Server 2012/2014
- 70-462: Administering Microsoft SQL Server 2012/2014 Databases
- 70-463: Implementing a Data Warehouse with Microsoft SQL Server 2012/2014
- 70-464: Developing Microsoft SQL Server 2012/2014 Databases
- 70-465: Designing Database Solutions for Microsoft SQL Server
- 70-466: Implementing Data Models and Reports with Microsoft SQL Server
- 70-467: Designing Business Intelligence Solutions with Microsoft SQL Server
- 70-743: Upgrading Your Skills to MCSA: Windows Server 2016
- 70-761: Querying Data with Transact-SQL
- 70-762: Developing SQL Databases
- 70-764: Administering a SQL Database Infrastructure
- 70-765: Provisioning SQL Databases
- 70-767: Implementing a Data Warehouse using SQL
- 70-768: Developing SQL Data Models
- 70-777: Implementing Microsoft Azure Cosmos DB Solutions
- 70-778: Analyzing and Visualizing Data with Microsoft Power BI
- 70-779: Analyzing and Visualizing Data with Microsoft Excel
As you can see, it's quite a substantial list! If you are already studying for any of these exams make sure to write them before the retirement date, June 30th. [Update: revised retirement date is March 30, 2021]. Otherwise, you should switch to a corresponding role-based certification and just study for that. The only tricky learning scenarios would be those that focus exclusively on on-premise products. New role-based certifications are still focused on Azure only, or on hybrid cloud scenarios.
You can learn more about the retirement of MCSA, MCSD and MCSE here.
The other recent change from Microsoft is the introduction of "Azure Database Administrator Associate" and "Data Analyst Associate" certifications. These would undoubtedly prove very popular once they are released to market. Each certification requires passing a single exam. The exams are scheduled to go to beta in the 1st week of April. More details on these upcoming certifications are here.
Here's an extract showing the suggested mapping of the legacy MCSA/MCSE certifications to these 2 new options:
Now that we've caught up with the most recent developments, let's now look at the entire Data & AI certification stream! There are 7 certifications:
- Azure Fundamentals
- Azure Data Scientist
- Azure Data Engineer
- Azure AI Engineer
- Azure Solutions Architect
- [April] Azure Database Administrator
- [April] Azure Data Analyst
These are the same because at both the fundamental and expert levels the IT professional should have a broad understanding of both Apps & Infrastructure and Data & AI concepts. And we've just talked about the new #6 and #7 certifications. So let's focus on the overall picture, certifications #2-#4 and a few other interesting non-certification learning options.
Below is a chart showing the overall progression path for the Data & AI certification portfolio. As you can see, there are no specific prerequisites from a certification standpoint. If you have the required knowledge you can write an exam for a Data & AI certification at any level right away.
Per the role-based certification approach, the Data Engineer Associate, Data Scientist Associate and AI Engineer Associate certifications closely correspond to similarly-named roles in the industry. These roles may be new to many of you (DBAs, data developers and similar titles are still more familiar in most organizations), so it's helpful to define them. An excellent description with Venn diagrams is available here. It very clearly explains the overlap between each role and that can help you decide the role that best fits your job responsibilities and thus the certification(s) to pursue. Each certification at the Associate level except Azure Data Engineer requires passing just a single exam.
In addition to these certification options, Microsoft also has a growing collection of learning paths that do not result in certification. These may be useful to you because they are often smaller in scope and may in certain cases better match your learning goals. These options include:
- Migration-focused courses
Here are the migration courses that are available today:
These are excellent ways to learn how to take your existing data assets and move them to Azure. This could be done as part of a full transition to the cloud or as part of a hybrid infrastructure solution. The DP-050 course is especially popular as just about every organization today has relational database deployments, whether those are based on SQL Server, Oracle, DB2 or other vendor products.
Microsoft Cloud Workshops (MCWs) are hands-on, 1-day sessions where you get a chance to go through a case study and implement an end-to-end scenario in Azure. These differ from a traditional course in which you may get a 50/50 balance of exercises and lecture. The workshops are almost all hands-on exercises, with the instructor taking on more of a coach role. Many of these MCWs cover technologies in the Data & AI space. Learning Tree can arrange to present any of them for your organization.
So that's the state of Data & AI certifications today. Five certifications in-market, two coming up next month and 2 non-certification learning options available on top of that! I hope this review gave you extra motivation to pursue these certifications and learning options. Never stop learning and best of luck with your study efforts.