Certification goals for 2023

This year (2023) my role at Cobalt Analytics will evolve a bit more as we grow. I will become more focused on the sales, architecture and training parts of the business and as such need to grow my knowledge of not only our core technologies but also the environments in which these technologies operate.

I’m setting myself the goal of obtaining 12 new certifications this year which breaks down to a very convenient 1 per month although I do not expect to complete them at that cadence. Many of these certifications will be in our core focus area of data engineering and analytics on the Microsoft platform but I would also like to take at least one competing product certification. Below I have listed the 12 certifications\exams that I plan to take although I expect this to evolve over the year. I’m also including my reasoning for taking the exam so if you see any flaw in my reasoning feel free to leave a comment.

1) AZ 305 : Designing Microsoft Azure Infrastructure Solutions 

My first exam for the year needs to be Microsoft AZ-305 Designing Microsoft Azure Infrastructure Solutions. Last year Microsoft changed its partner system such that partners needed to obtain more than a handful of technology-focused exams. and one of those changes was the introduction of two prerequisite exams, AZ-104 and AZ-305. I wrote the AZ-104 exam last year and need to rewrite the AZ-305 this year.   

Completed on 10 Jan 2023

2) Databricks : Data Engineer Associate

At cobalt Analytics we want to grow our supported tech stack to include Databricks. There is great demand both locally for Databricks implementations both locally and abroad and we need to make sure that we are up to the challenge of embracing this growing technology. I completed the fundamentals exam and the data analytics exam last year and would like to grow and affirm my skills in the data engineering side of the tool.

Completed on 20 Jan 2023

3) Databricks : Apache Spark Developer Associate

The Apache Spark exam focuses on your understanding of the Spark DataFrame API which is the foundation of both Spark and the Databricks offering. I believe that this exam will fit in nicely between the associate and professional data engineer exam

4) Databricks : Data Engineer Professional

Following on from the associate exam I would also like to write the Professional exam. 

5) Databricks : Machine Learning Associate

Machine learning is not an area that we focus on but keeping our eye on the horizon I will also be taking on the Machine learning features in Databricks. As this is an associate exam I plan to take this in the first quarter of 2023 to start the journey. 

6) Databricks : Machine learning professional

The final Databricks exam I plan to take is the Databricks machine learning professional exam. this will no doubt be the most difficult exam I plan to take this year. while I am familiar with many machine learning concepts it is not my strong suit. as such I expect this exam to be the last one I write this year and if I fall behind will probably be the first to fall off the list. That’s not to say it is not important but I am willing to give myself more time to become familiar with the topic if need be.  

7) DP-500 : Designing and Implementing Enterprise-Scale Analytics Solutions Using Microsoft Azure and Microsoft Power BI

The DP-500 exam is one of the newest exams, as it focuses on Power BI, a technology I have a lot of experience I do not see this being an overly challenging exam. That’s not to say I will not need to do some preparation but I’m assuming (famous last words) that this one will be one I could write

8) AI 102 : Designing and Implementing a Microsoft Azure AI Solution

One of the focuses of the year will be to ensure that I am up to date with all the data & AI exams and the AI-102 is another exam that I need to complete, the AI 102 exam looks at testing your knowledge of all Microsoft’s prebuild AI tools collectively known as the Azure cognitive services. This exam is less about understanding the implementation of these tools but rather their use as most of them use APIs.

9) DP 100 : Designing and Implementing a Data Science Solution on Azure

The DP 100 looks at your ability to apply your machine learning solutions on Azure infrastructure. A large part of this exam looks to be machine learning in Databricks so will complement my certifications in Databricks machine learning. 

10) DP 420 : Designing and Implementing Cloud-Native Applications Using Microsoft Azure Cosmos DB

The DP 420 exam focuses on Azure Cosmos DB which is a collection of data stores including key-value, column, document, graph and now relational databases. While this exam does not address analytics and is more of a developer exam, Cosmos DB is a growing source of data and understanding the platform will no doubt be crucial. 

11) DP 300 : Administering Microsoft Azure SQL Solutions

The DP 300 exam looks at building database solutions on Azure SQL databases, SQL is still a major source of data for analytics and is very capable of supporting analytics workloads itself.

12) Snowflake : SnowPro Core Certification

Finally, I want to add a none Microsoft exam to my list of skills, even though I do not do any work on Snowflake, it is easily the largest competitor in the analytics space to Microsoft so having a better knowledge of its strengths and weaknesses can only be a good thing.

This is certainly a lot of exams and I’m being very optimistic in believing that I can complete them all. but as they say, if you aim high and miss you have still done well. Completing less than 8 of these exams would be disappointing. I plan to update this page every time I complete one of these exams and also hope to do a small writeup on each one sharing things that worked out well for me.

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