Challenge: 'AWS Certified Data Analytics Specialty' in 30 days [before to be retired - April 9, 2024]

TLDR

I wrote this article in first place in my own blog, https://www.playingaws.com/posts/challenge-data-certification-in-30-days/, but I want to post it here to expose it to all interested people!

The AWS Certified Data Analytics Specialty is going to be retired on April 9, 2024. You still have time to do it. However, you have another option, AWS presented a new Data certification of the Associate level, AWS Certified Data Engineer, you have more information here.

If you are here, it's likely because you're eager to obtain the certification, or perhaps you're curious about the insights I've shared in this guide!

In either case, rest assured that this guide is a firsthand account of my successful journey to achieve the AWS Certified Data Analytics Specialty certification. I conquered the exam on October 15th.

If I could do it, you certainly can too.

I didn't have experience in data analytics (not enough) and neither specific knowledge, but I wanted to prepare the certification because I wanted to get more knowledge in this area. I am a Cloud & Solutions Architect who wanted to know how to design, build, secure, and maintain analytics solutions using AWS tools and services. However, this certification is not easy and I had to dedicate a lot of hours to be prepared to pass the exam.

I will use in this article [30 days] to prepare the certification's journey. However, remember, everyone's learning pace is different. Adjust the suggested plan based on your comfort level and progress. You could need more or less than 30 days.

Introduction

Welcome to the challenge of achieving the AWS Certified Data Analytics Specialty certification in just 30 days!

In this article, we will embark on a journey together to prepare for and conquer this certification. Whether you are an AWS Solutions Architect or a data enthusiast looking to expand your knowledge and credentials, this challenge will provide you with the guidance and resources needed to succeed.

Good luck with your certification journey!

Challenge: 'AWS Certified Data Analytics Specialty' in 30 days

I wrote this other article about 10 steps to prepare any AWS Certification, and I will follow those 10 steps in this challenge. This is the summary:

1. Find the proper certification for you
2. Find your WHY: Motivation is the key
3. Create a study plan
4. Take the official AWS Exam Readiness course
5. Choose a main training course
6. Practice using the AWS console to gain hands-on experience
7. Read the recommended whitepapers
8. Read the recommended FAQs
9. Take your own notes (and study them)
10. Practice with exam-style questions (tests)

Day 1: validate that the Data analytics certification is right for you and know what is your motivation (WHY)

Validate that the certification is right for you (step 1)

• [x] Read exam guide

In this challenge, our goal is to obtain the AWS Certified Data Analytics Specialty certification, so it is important to carefully read the exam guide and ensure that this certification aligns with your goals and aspirations:

• Data Analytics exam landing page
• Data Analytics Exam guide

• [x] Decide if you want to achieve the certification

I am far from being the target candidate described in the exam guide:

The target candidate should have 5 years of experience with common data analytics technologies. The target candidate also should have at least 2 years of hands-on experience and expertise working with AWS services to design, build, secure, and maintain analytics solutions.

It means that I need to intensify my efforts and commence my journey with a solid grasp of the essentials.

Motivation (step 2)

• [x] WHY?

Before starting, you must have a very good reason to do it, good enough to not quit in the middle.

What are your reasons for getting this new AWS certification?

In my case, I need the Data certification because I don't have as much experience in data projects as I want, and I truly wanted to learn how to design, build, secure, and maintain analytics solutions using AWS tools and services so that I can collaborate in a helpful way on data projects. The second reason is because the data certification is the nearest one to an event driven solution, and I want to be involved in this solutions in the future.

Your motivation is your WHY. How powerful to you is your WHY to you?

If it is not good enough, probably you are going to give up...

Day 2: Target date, buy the exam and create the study plan (step 3)

• [x] Purchase the exam

My target date was one month away, so I purchased the exam to do it even more real. I usually set a target date and buy the exam to motivate myself. Don't worry, you can always reschedule the exam twice for free with at least a minimum of 24 hours prior notice. I had to reschedule exams several times, but it is a good idea have a date in mind from the beginning.

I strongly recommend you request the time extension of 30 minutes if English is not your mother tongue.

• [x] Create a study plan

Like I said, we will follow these 10 steps to prepare any AWS Certification.

You have to allocate time to prepare the exam. When creating your study plan, it is important to be realistic about the amount of time you can commit to studying. Be sure to factor in other commitments, such as work, family, and social obligations.

Probably your plan will change and you need to be flexible, but it is a good idea try to plan all the things you want to do to prepare the exam.

These are all the tasks that I had to do to prepare the exam, with an estimated amount of time [updated: I had to spend more hours in practically all the tasks]:

• 8h: Learn the basics of data analytics
• 4h of online content (so I will spend at least 8 hours)
• Xh: Take a main training course. I will left here different options for you (there are many many more).
• 4h (my estimation) - Whitepapers:
• 5h (my estimation) - FAQs
• 20h (my estimation) - Practice with the main services (list above)
• 8h (my estimation) - Take my own notes and study it
• 8h (my estimation) - Practice exam questions

Day 3 - Starting with the basics

• [x] Introduction to AWS Data Analytics

In my case, I had to start with the basics, so I decided to spend one full day and also writing this article about the Introduction to Data Analytics.

Initially I have included all the information in the same article but it was too long so I decided separate, also because maybe you are not interested in the introduction to the Data Analytics!

Days 4-6 - Exam readiness (step 4)

• [x] Exam readiness

Take the time to go through the Exam Readiness: AWS Certified Data Analytics Specialty course provided by AWS. This course is specifically designed to help you prepare for the exam and covers important topics, including domain areas, question formats, and exam strategies.

AWS always show one message similar to this one: This is NOT training. This is to complement your training....
{: .prompt-warning }

These are the five domains for this certification. Four of them are the same that the Process of Data Analytics mentioned above + Security domain.

• Collection (18%)
• Storage and data management (22%)
• Processing (24%)
• Analysis and visualization (18%)
• Security (18%)

Let me show the main AWS Services for each domain, and let me show you the more important ones.

Domain 1: Collection

Focuses on ingesting raw data from transactions, logs, and Internet of Things (IoT) devices.

Main AWS Services

• Amazon Kinesis Data Streams
• AWS Glue
• Amazon Kinesis Data Firehose
• AWS DMS
• Amazon SQS
• AWS IoT
• AWS Snowball
• Amazon MSK

Domain 2: Storage and Data Management

Main AWS Services:

• Amazon RDS
• Amazon Neptune
• Amazon DynamoDB
• Amazon Redshift
• Amazon ElastiCache
• Amazon S3
• AWS Lake Formation
• Amazon Aurora

Domain 3: Processing

The goal of the processing system is to transform data and make it more consumable by analytics and visualization tools

Main AWS Services:

• Amazon EMR
• Amazon Kinesis Data Analytics
• AWS Glue
• AWS Lambda
• AWS Step Functions
• AWS Data Pipeline

Domain 4: Analysis and Visualization

The analysis and visualization domain is about using the data you've collected, processed and transformed to generate actionable insights.

• Amazon Athena
• Amazon Kinesis Video Streams
• Amazon OpenSearch
• Amazon EMR
• Amazon Redshift
• Amazon kinesis Data Analytics
• Amazon SageMaker
• Amazon QuickSight

Domain 5: Security

Main AWS Services:

• AWS IAM
• AWS KMS

• Check encryption of the following services: S3, Redshift, Kinesis, EMR and Glue

• [x] Take my own notes

I take notes of all the videos/material I think it is useful so after that I can check it again. Sometimes is just do an screenshot of something important and sometimes I take my own notes.

Days 7-17 - Main training course & Practice resources (step 5 & 6)

First of all, I think you have to check this AWS resource: Ramp-up data analytics. This is a recompilation of many other courses and AWS content related with Data Analytics.

• [x] Main training course

You have to select your own training course. Here, if you select one course that covers all the certification content you will save a lot of time searching for additional resources.

Some examples:

• 17h of content: Udemy [not free course]
• 42h of content: Cloud Academy [not free course]
• AWS SkillBuilder courses [not free courses]

In my case, I selected SkillBuilder resources because I wanted to test this platform. Also, I don't wanted to watch training videos... I preferred choose all downloadable content and online content, and take my own notes to check them later. However, there is no one official preparation course in the SkillBuilder platform, so I had to select a few resources to try to cover all the content (and definitely I had to invest more time).

Disclaimer: these are not free courses. If you are only looking for free content, you can search yourself a free main training course or you can omit this step. However, probably you have to compensate with MANY more hours of preparation to fill all the gaps you have and to cover all the certification content

These are a few courses I did in the SkillBuilder platform:

• Data Analytics on AWS (Technical), 4h. Digital content (no videos)
• AWS Partner Certification Readiness: Data Analytics - Specialty (18h 27m). It includes pdf material that you can download, very useful! I didn't check the videos... only the pdf content! Also, this is a readiness course...
• Data & Analytics Tech Talk (Partner Learning Plan), 10h 32m. Again, it includes pdf content that you can download, very useful! It contains 8 different courses
  • Transform your data approach: Develop a modern data strategy - Technical
  • Better, faster, and lower-cost storage : Optimizing Amazon S3 & FSx/EFS storage - Technical
  • Analytics Readiness for BFSI - Technical
  • Transactional data lakes on AWS - Technical
  • Serverless Data Integration for a Modern Data Infrastructure with AWS Glue - Technical
  • Analytics on SAP Data - Technical
  • Redshift Migrations & POCs - Technical
  • Right Data Streaming Architecture for your Streaming Analytics

• AWS Cloud Quest Data Analytics. AWS Cloud Quest is the only role-playing game to help you build practical AWS Cloud skills. The challenges were easy and you have to complete many very un-useful challenges related with other services not related with the Data Analytics certification, but it was funny! I completed all the challenges and I achieved the AWS Cloud Quest Data Analytics badge

• [x] Practice

Follow a training course is highly recommended but practice with the AWS console is even more useful to retain information. And much more if you don't have much experience with some of the AWS services.

I experiment by myself directly with some of the AWS services but I also get some internet examples.

I used these Skill Builder labs to practice with the main AWS resources in a provided AWS account.

Again, there is A LOT of free content you can check... Here are a few examples:

1. Build and automate a serverless data lake using an AWS Glue trigger for the Data Catalog and ETL jobs
2. Game Analytics Pipeline
3. Serverless Analytics for Games
4. Create business intelligence dashboards with Amazon QuickSight: https://aws.amazon.com/getting-started/hands-on/create-business-intelligence-dashboards-using-amazon-quicksight/?p=ft&c=aa&z=4)
5. Orchestrate Amazon EMR Serverless jobs with AWS Step functions
6. Modernize a legacy real-time analytics application with Amazon Managed Service for Apache Flink
7. Using AWS AppSync and AWS Lake Formation to access a secure data lake through a GraphQL API
8. Build event-driven architectures with Amazon MSK and Amazon EventBridge
9. Securely process near-real-time data from Amazon MSK Serverless using an AWS Glue streaming ETL job with IAM authentication
10. Introducing Amazon MSK as a source for Amazon OpenSearch Ingestion
11. Generate security insights from Amazon Security Lake data using Amazon OpenSearch Ingestion
12. End-to-end development lifecycle for data engineers to build a data integration pipeline using AWS Glue
13. Build and share a business capability model with Amazon QuickSight

Days 18-19 - Whitepapers (step 7)

The link of the official AWS Whitepapers is included in the documentation landing page:

• Amazon EMR Migration Guide: How to Move Apache Spark and Apache Hadoop From On-Premises to AWS
• Big Data Options on AWS
• Streaming Data Solutions on AWS with Amazon Kinesis
• Teaching Big Data Skills with Amazon EMR
• Reference Architecture: SQL Based Data Processing in Amazon ECS

Days 20-21 - FAQs of the main services (step 8)

The link of the official FAQs is included (again) in the same documentation landing page:

• Amazon Athena
• Amazon EMR
• Amazon Redshift
• Amazon CloudSearch
• Amazon Kinesis
• Amazon Kinesis Data Streams
• Amazon Kinesis Data Firehose
• Amazon Kinesis Data Analytics
• Amazon ElasticSearch Service
• Amazon Managed Service for Kafka (MSK)
• Amazon QuickSight
• AWS Data Exchange
• AWS Glue
• AWS Lake Formation
• AWS Data Pipeline

Days 22-24 - Study my notes (step 9)

Unfortunately I cannot share my own notes, but I used this time to check everything again and again.

Days 25-29 - Practice with exam-style questions (step 10)

You have many options on internet.

The 2 AWS official test resources are the following:

• 10 questions - AWS Certified Data Analytics Specialty Sample Questions
• 20 questions - AWS Certified Data Analytics Specialty Official Practice Question Set

Day 30 - EXAM

A few advices that you already know... so, reminders!

BEFORE the exam:

• Sleep well the previous night to be rest in the exam. It will be a long exam with long questions...

DURING the exam:

1. Identify keywords in the questions
2. Eliminate wrong answers
3. If you have doubts, answer the question, write in the comments your possible answers and everything that will help you in your next revision (example: A or B doubt in xxxxx), flag it, and go to the next one
4. Don't spend to much time on each question. 3 minutes if you have requested the additional 30 minutes for non-native english speakers
5. Review all the flagged questions and un-flag the ones that you are more confident now
6. Review again

With all the work already done, you only have to do the exam and pass it!

One last thing! If you followed this guide or found it helpful, let me know in the comments, or you can access to my blog to find more AWS useful content! https://www.playingaws.com/