AWS Specialty Certification as a Product Manager

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This week’s post is about my journey of taking a certification for which I have none of the requirements for! We will dive into the challenges and benefits of taking a AWS Specialty Certification as a Product Manager.

On our Q4 Roadmap Planning, we decided to have a strong learning component. The idea was to take an AWS Analytics Specialty Certification and report on the process, the benefits, the challenges and most importantly the possible shortcuts!

Why a specialty certification as a product manager?

AWS certifications are probably not the go to learning for a product manager. Nevertheless, it makes sense to ask: why not?

I admit: I am suspicious. I have a technical background: a technical degree, a career start as a developer and even a software architect experience (very specific around advertising, but still counts). Software engineering and architecture are not new worlds for me. In addition, I am also a proud Jack of all trades who likes to have a deeper understanding of the technologies I am working on, than I may need to.

Not all product managers need to have technical skills, it is often not their focus. Their learning time is usually best spent in learning product management frameworks and tools, learning more about their specific markets and industries and even on getting formal management certifications like an MBA. But would it hurt for product managers to have certifications on the technologies used on their projects? Probably not.

Regardless of having technical certifications, there are products/projects that are very technical in nature. The product manager’s contribution on breaking down stories, establishing a roadmap and even accessing granular priorities is deeply linked to domain knowledge she or he has n the project. Data projects usually fall into the technical category, especially at the genesis on a new data stack.

If you are looking for other opinions on the topic, check out Eric Weber – Head of Data Product and Experimentation at Yelp, he has a great post on the subject.

A more wary reader may ask: “Ok, a technical certification may be useful, but why prioritising that over formal Product Management training?”. Good question Mr(s). Reader! At this point in time, I felt this was what served my current role best. I am definitely interested in looking at other training more focused on product management. Keen to hear Mr(s). Readers opinion on essential Product Management training. I will leave my personal opinion on that topic for another post.

Why AWS?

I have previously worked on a Data Project that was deployed on a bare metal Cloudera stack. Even though it was a great learning experience and an interesting raw intro to the world of Big Data, the project had a number of challenges related to the environment. If at the time we had the option to choose where the stack was going to land, we probably would have chosen to go with a cloud vendor. Aligning cloud and big data knowledge/skills is a good booster to be able to contribute on nowadays Big Data projects.

Looking at the specific challenges in front of me at this point, AWS was a natural choice for the cloud component. AWS has solutions for different types of databases, data lake, date warehouse, collection and even analytics and visualization. They may not always be the best tools, but from an architectural perspective it is interesting to have reference points. For example, AWS has a service for object storage called S3, its core use is reliably keeping files stored without worrying about performance, scalability, availability, and durability. Azure, GCP and other cloud providers have similar technologies and there are even open source solutions to achieve the same goals. Having a reference technology for a given purpose and understanding how it fits into a data stack, provides context of what is needed to build a data architecture.

The Course

The AWS Data Analytics – Specialty courses are designed to prepare students to take the homonym AWS certification. I had an existing access to Linux Academy, so I decided to start a course there.


AWS has 4 certification levels:

  1. Foundational-level AWS Certifications
  2. Associate-level AWS Certifications
  3. Professional-level AWS Certifications
  4. Specialty AWS Certifications

The list above is ordered from entry-level and broad to advanced and specific. The AWS Data Analytics Certification is a specialty certification (number 4 on the list). This means that this certification is among the most advanced and specific certifications AWS has.

  • At least 5 years of experience with data analytics technologies
  • At least 2 years of hands-on experience working with AWS
  • Experience and expertise working with AWS services to design, build, secure, and maintain analytics solutions

Even though none of the above are hard requirements, these should not be taken lightly if you wish to take the test. Taking the the test has a cost of 300$, non-refundable. There is a 150$ discount if you have another certification, nonetheless it is better to be certain of your knowledge, before signing up for the test.

As mentioned above I have worked as a data product manager before. It was an interesting project where we actually had to design a data stack from top to bottom. I have learned a lot on that project, but I have only worked on it for about 2 years, less then the 5 required. I have close to no experience on AWS, both on designing applications or using it at all.

Bottom line, I have none of the requirements from the list, but this Idea Shortcut is all about shortcuts (see more below). Learning will be no different. To make sure I was not super far from being able to understand the concepts of the course, I decided to answer a number of questions on a test exam, prior to get the classes to see how did. I have recorded my trial run, which I will upload on our youtube channel, another project that we are working on.

UPDATE: Here is the video


The exam covers 5 domains of knowledge: Collection [18% of the exam score]; Storage and Data Management [22% of the exam score]; Processing [24% of the exam score]; Analysis and Visualization [18% of the exam score]; Security [18% of the exam score ].

Data Stack Building Blocks
Data Stack Building Blocks

We have created a page with a short summary of the description of each domain to understand what is covered. While doing this exercise we realized that the list of domains covered on the AWS exam is also a great checklist of items to review on any data stack architecture. So much so, that we decided to use this in the page name:

DATA STACK CHECKLIST (and AWS Analytics Specialty Certification domain overview)

The fact that the certification is so thorough proves our point earlier about AWS being a great reference point for data architectures.

In parallel, with the different domains covered in the certification AWS also provides a list of AWS services and features that may be included in the final test. Note that the services that may be covered in the exam do not fully match the Linux Academy course syllabus. Some of these services, especially the ones that are not data specific, are covered on other courses. We have prepared a page where you can see the comparison between the services and features that can appear on the exam, and the ones on the Linux Academy course syllabus.


Read more about the certification content here. Read more about the Linux Academy (now Cloud Guru) course here.

Linux Academy

AWS does not provide Linux Academy has recently been acquired by Cloud Guru and they are migrating the accounts to the new service. It is possible that I start the course on one service and finish on another. Linux Academy has comprehensive video courses which can be visualized on decent platform. The most interesting part of the service are the sandbox environments that allow you experiment straight on AWS services with no extra charge. Labs are done on this environment too, so while you are taking the course you are getting the real life experience of using the service. In addition, for certification courses Linux Academy also provides at least one practice exam which is very useful to test your knowledge. Taking a practice exam from AWS itself costs 40$ and there is no certification if you pass. Here is a list of other interesting features taken from Linux Academy (now Cloud Guru) webpage:

  • Cloud Sandboxes
  • Hands-on Labs
  • Unlimited courses
  • Career learning paths
  • Quizzes and practice exams
  • Curated updates
  • Cloud Servers
  • Community forums
  • Mobile app

Progress and thoughts

I have established a course schedule. I decided to dedicate 30 mins per day during workdays to take the course, see below:

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Linux Academy Course Schedule Screen

With this availability, the course is expected to last 12 weeks. I will try to get through the course done by the end of October, 8-9 weeks in total.

At the moment I am not doing great:

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Linux Academy Course Progress Screen

I should be around the 40% mark at this point, but I am at 14%, mostly because I have not been able to dedicate 30 mins each day. However, I am determined to pick up the pace and make up for the time lost. Still confident I can meet the deadline.

At this point, I have watched all the lessons dedicated to S3 and did the lab. The video lessons have been easy to get thus far and the lab was easy to follow. For the S3 part a big potion of the lessons was spent reviewing the python SDK (Boto 3) to upload, delete and manage objects in S3. If you do not plan to work with python, there is possibly a few parts you can skip. From what I gathered the certification is programming language agnostic, so it is not expectable to get python coding questions, even considering that Boto3 is an AWS SDK.


As mentioned above, Idea Shortcut is all about shortcuts. Learning shortcuts can be challenging, for this certification in particular it is important to figure out what is that you want to take from the it:

Do you just want to have the badge?

In this case, you can focus purely on what it takes to pass the exam. I would recommend reading all the FAQs and product pages of the services that can appear on the exam, see here. I would skim through or even skip most video training lessons and labs from Linux Academy. Finally, I would do as many practice exams as I could possibly lay my hands on. To reduce the consequences of taking the exam, I would probably first take an entry level exam to get the discount and get base knowledge on IAM, Networking and other base AWS functionality, which is not well covered on the specialty training.

Do you want to be ready to architect data systems?

In this case,cI would also recommend doing some light reading through the FAQs and product pages of the services that can appear on the exam, see here. I would not put as much effort on this as if you would be taking the exam. You do not necessarily need to memorize all details, you can always refer to this documentation later when designing systems.

I would pay more attention to the video lessons but I would just skim through the labs.

(I fall on this category personally)

Do you want to be ready to implement data systems yourself?

In this case the biggest focus should be the Linux Academy course labs and their Cloud Sandbox environments. I would review the course slides before committing to watch a full video lesson. In addition, I would read the labs first and make sure I only watched the video lessons required to be able to do the lab.

(Side) Benefits

According to pluralsight. The benefits of obtaining this certification include:

  • Being able to participate in projects of high technical complexity related to issues of massive data processing.
  • According to ZipRecruiter, the annual salary of someone with the AWS Certified Data Analytics – Specialty certificate on average reaches US $ 123,807, or more with additional experience and certifications.
  • Recognition from the industry and your colleagues
  • Direct benefits from AWS, such as discounts on practice tests or other certifications in addition to badges that you can use in your presentations, resumes, or other instances where you want to prove your experience.
  • Qualification for better jobs; the certification is valid anywhere in the world.

Progress and Resources

Follow my progress and check the resources we are using on the on our Public Roadmap at: