Your guide to the AWS Data Analytics certification

By Danny Aspinall

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Studying for an Amazon Web Services (AWS) Data Analytics certification? Or maybe you’re still wondering if a certification is the best move for your career? You’re in the right place.

Whether it’s learning new skills, reaffirming your expertise, or helping your resume stand out from the crowd, there are many ways certifications can help to bolster your career progress and prospects.

But becoming AWS certified in data analytics is no easy feat; it takes a considerable amount of time, dedication and expertise.

That’s why we’ve put together this guide. Exploring how and why to earn an AWS Data Analytics – Specialty certification, we’re covering all the fundamentals and offering handy tips on studying, preparation, and assessment along the way.

What is the AWS Data Analytics certification?

The AWS Data Analytics certification, formerly the AWS Big Data – Speciality certification, is awarded to candidates who successfully complete the AWS Certified Data Analytics – Specialty (DAS-C01) exam.

The certification is designed to validate a professional’s understanding of using AWS services to design, build, secure, and maintain analytics solutions that provide valuable data insights.

It’s also intended to test a professional’s understanding of:

  • AWS data analytics services and how they integrate with each other
  • The roles AWS data services play in the lifecycle of data collection, storage, processing, and visualization

Of the AWS professionals surveyed in the latest Jefferson Frank Careers and Hiring Guide: AWS Edition, just 7% held the AWS Certified Data Analytics – Speciality certification, making this an effective way for relevant candidates to get ahead of their competition.

Who should obtain an AWS Data Analytics certification?

The exam scope isn’t intended for novices. In fact, the AWS Data Analytics certification is aimed at professionals with considerable experience and expertise with cloud analytic solutions.

Before you take the exam, AWS recommends that you have:

  • A minimum of five years of experience with common data analytics technologies
  • A minimum of two years of hands-on experience and expertise working with AWS analytics solutions

This experience and expertise isn’t compulsory; there are no required prerequisites for sitting the exam. However, these recommendations are a good indication of the depth of skill and knowledge required to pass the exam and receive the certification.

With this in mind, which professionals should be looking to earn an AWS Data Analytics certification?

Data analysts and data scientists

As the name suggests, data analysts and data scientists no doubt benefit most from obtaining an AWS Data Analytics – Speciality certification.

Data professionals already working within AWS can reaffirm their existing knowledge on data collection, storage, processing, and visualization. They can also expand their expertise building complex data models augmented with the latest AWS tools.

Data analysts and scientists not currently working within the AWS ecosystem will also benefit from the research and upskilling required for this certification. By becoming AWS certified in data analytics, professionals can broaden their horizons by learning how AWS extensions, applications, and tools can be used to modernize and revolutionize their existing data approach.

Database Administrators

Database administrators may benefit from an AWS Data Analytics – Speciality certification, depending on how much they’re involved in data analysis and visualization.

While there are more specialized certifications suitable for administrators who mostly work maintaining data storage options and solutions, the AWS Data Analytics certification can assist in the comprehension of data and infrastructure concepts.

This means conversations around data can be clearer and better informed, contributing to more beneficial practices and decision making.

Solutions Architects

Becoming AWS certified in data analytics can be useful for solution architects looking to hone their experience and expertise towards data architecture.

The knowledge gained completing the certification well equips solution architects looking to become subject matter experts in analytics solutions and modeling approaches, helping them better understand how to improve data environments using AWS.

Like all AWS certifications, earning the AWS Data Analytics – Speciality isn’t a necessity for securing a job in one of these roles. However, it can help candidates to stand out in a competitive market when job hunting; a belief 84% of AWS professionals shared in the Jefferson Frank Careers and Hiring Guide.

Other advantages to undertaking a certification listed by AWS professionals included:

  • A way to verify skills
  • Better career progression opportunities
  • Increased job efficiency
  • Recognition from employers that skills adhere to a professional standard
  • Increased industry knowledge
  • More trust from employers

Better yet, our polling showed that professionals who become AWS certified in data analytics are 23% more likely to receive a pay increase.

As a result, the AWS Data Analytics certification is suited to relevant candidates looking to make the most of existing opportunities or open new doors within the AWS ecosystem.

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How to earn an AWS Data Analytics certification

It costs $300 to take the AWS Certified Data Analytics — Specialty exam.

Those currently in work should ask whether their employer will contribute towards the cost of the certification. Of the 77% of AWS professionals in the Careers and Hiring Guide who had or were working towards a certification, 48% had their certifications paid for in full by their employer. A further 17% received partial funding.

The exam is delivered either at an in-person testing centre or as an online proctored exam. Those opting to sit the exam remotely will have additional rules to adhere to, including:

  • Not leaving the room or allowing any disruption from either you or a bystander
  • Taking the exam on a Windows or macOS machine with active camera and microphone
  • Keeping no phones, snacks or beverages within reach
  • Facing your camera head-on

You have 180 minutes* to complete an exam of around 65 questions. 50 of these question will affect your score; the other unscored questions are placed on the test to gather statical information and have no impact on your total score.

The exam features two question types:

  • Multiple choice: these questions offer a choice of four responses. One is the correct response, while the other three are incorrect ‘distractors’.
  • Multiple response: these questions offer a choice of five or more responses, two or more of which are correct. The remaining incorrect answers, the ‘distractors’, tend to be plausible responses aimed at catching out candidates with insufficient expertise and skill.

The exam is scored as a pass or fail using a compensatory scoring model, with the pass benchmark sitting at a minimum of 750/1000. This means you don’t need to pass each individual section of the test, just the overall exam.

*Non-native English speakers can apply for an additional handicap of 30 minutes.

AWS Data Analytics: the fundamentals

It’s important to familiarize yourself with the fundamentals of the AWS Data Analytics certification to ensure you have sufficient base-level knowledge and skill to succeed.

A good place to start is the exam’s content outline. While not a comprehensive listing, AWS provides an invaluable insight into the main areas of focus and the weighting given to each:

  1. Collection – 18% of the exam
  2. Storage and data management – 22% of the exam
  3. Processing – 24% of the exam
  4. Analysis and visualization – 18% of the exam
  5. Security – 18% of the exam

Products and services you should have a comfortable knowledge of include:

  • EMR
  • Redshift and Redshift Spectrum
  • Kinesis Data Streams, Kinesis Firehose and Kinesis Analytics.
  • S3+Glue+Athena
  • Amazon MSK
  • Simple Queue Service (SQS)
  • AWS Database Migration Service (DMS)
  • Simple Storage Service (S3)
  • DynamoDB
  • AWS Lambda
  • MapReduce
  • Amazon Elasticsearch Service
  • Relational Database Service (RDS)
  • Quicksight

To avoid over-studying, it’s also important to familiarize yourself with what you’re not expected to know when taking the AWS Data Analytics certification. Areas considered out of scope for the exam include:

  • The design and implementation of machine learning algorithms
  • The implementation of container-based solutions
  • The utilization of high-performance computing (HPC)
  • The design of online transactional processing (OLTP) database solutions

AWS Data Analytics certification: preparation tips

When preparing to sit the exam, it’s recommended that you learn the most important concepts and components of data analytics technologies in thorough detail.

While this may sound obvious, it can be tempting to instead rely on practice tests or even ‘exam dumps’ as a revision approach. However, these rarely equip you with the confidence and expertise required to succeed.

Instead, take the time to deep dive into valuable resources like white papers. AWS recommend the following white papers for candidates preparing for the AWS Data Analytics certification:

Before sitting the exam, it’s also recommended that you test your AWS Data Analytics certification prep with AWS’ free course: Exam Readiness: AWS Certified Data Analytics — Specialty. There are plenty of links and resources offered up in this course that are great for reaffirming what you’ve learned and brushing up on any weaker areas.

It’s also worth cross-checking your preparation against the AWS Certified Data Analytics – Specialty exam outline to ensure your revision has covered all necessary bases.

Tips for passing the AWS Certified Data Analytics — Specialty exam

When you sit the exam, take the time to carefully read each question, and ensure you confidently comprehend what’s being asked.

Now, we know what you’re thinking: that’s hardly expert advice. But in the AWS Certified Data Analytics — Specialty exam, applying a methodical approach to how you digest each question can help simplify each task.

First, identify the keywords. These are the words or phrases embedded within the question that prompt your direction and reasoning. Common examples of these keywords include:

  • most cost-effective
  • minimize administrative tasks
  • minimal coding effort
  • minimal development effort
  • most efficient way

Cross-reference your keywords with the options available to identify the most relevant and accurate answer(s).

Be sure to adopt the right mindset before committing to your answer, too. Cloud best practices and culture can vary widely, meaning it pays to adopt an AWS way of thinking wherever possible. Ensure your reasoning always aligns with the best practices and culture of AWS.

If taking the test remotely via an online proctoring exam, be sure to make use of the virtual whiteboard feature to visualize your thought processes and methodology.

If you’re still unable to come up with an answer, guess. There are no penalties for guessing, but unanswered questions are scored as incorrect. So, when all else fails, hedge your bets and trust your instincts.

Earning an AWS Data Analytics certification can provide exciting opportunities for faster career progression and new career prospects in the AWS ecosystem. Explore what jobs are on the market today, and be the first to hear about the latest AWS opportunities by signing up for job notifications by email.

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