The value of data and pursuing the AWS Certified Data Analytics – Specialty certification
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Co-authors: Shefali Emmanuel, Aayzed Tanweer, and Manikanta Gona
Editor’s note: In this blog, AWS Solutions Architects Carole Suarez, Shefali Emmanuel, and Aayzed Tanweer, and AWS Associate Data ML Engineer Manikanta Gona, share their insights on the importance of data and share resources to pursue the AWS Certified Data Analytics – Specialty certification.
Across industries, organizations are in a transitional period of modernization, looking at how to advance their use of data to make strategic business decisions. Social media, finance, manufacturing, and transportation are some of the industries producing incredible amounts of data. With an increased focus on data analysis to drive business decisions, organizations are looking for individuals with the knowledge, skills, and expertise to help them make the most of their data. The U.S. Bureau of Labor Statistics sees strong growth for data science jobs skills in its prediction that the data science field will grow about 28% through 2026.
In this blog, we’ll explore how to build your skills and expertise in data analytics with specific resources to help you pursue and earn the AWS Certified Data Analytics – Specialty certification. Individuals who have at least five years’ experience with common data analytics technologies and two years’ hands-on experience and expertise working with AWS services to design, build, secure, and maintain analytics solutions are the ideal candidates for this certification.
Our experiences with data
Shefali Emmanuel, Industrial Manufacturing Solutions Architect at AWS
I help customers on various workloads, but I have yet to come across one that does not involve data. Data is at the heart of every project I’ve worked on to date, from data generation, to ingestion, to analysis. For this reason, I decided to embark on this journey to earn the AWS Certified Data Analytics – Specialty certification to build expertise that will allow me to understand how to derive value from data that has a wide scale of applicability to all customers going forward.
Carole Suarez, Startup Solutions Architect at AWS
I decided to learn more about data analytics because every single company we work with has data and not all of it is currently being used to drive business insights. I come from a mechanical engineering background, and through this I learned that traditional companies have CRMs, click-through data, sensor data, etc. that is untouched and/or unused. The ability to understand and coach startup organizations on the stages of data from ingest, to storage, to visualization and derive business insights, has been invaluable.
Aayzed Tanweer, Startup Solutions Architect at AWS
I’m exposed to a multitude of technology areas on a daily basis, ranging from machine learning to networking and edge compute. While I love the diversity and breadth of technology I get to work with, I wanted to work toward developing a specialty. I’ve always enjoyed data because it helps me connect technology with people. As such, pursuing a specialty in data analysis was the natural route for me. When I was starting on this journey, however, the vast amount of information out there made it difficult to find a streamlined path to follow. The AWS Certified Data Analytics – Specialty certification proved to be the perfect jumping-off point to embark on what I now believe will be a lifelong passion—data analytics!
Manikanta Gona, Associate Data ML Engineer at AWS
When I decided to change careers from Software Test Engineer to Associate Data ML Engineer, I was excited to explore data and analytics as I felt it provided me with a wide range of career opportunities. It was a natural choice to pursue the AWS Certified Data Analytics – Specialty certification as it helped me gain knowledge on what AWS services to use and when. By obtaining this certification, I learned varying customer solutions and use-cases, which set me up for success in my current Associate Data ML Engineer role.
How to prepare for AWS Certified Data Analytics – Specialty exam with AWS training resources
AWS Training and Certification has a multitude of resources to help you skill up and prepare for the AWS Certified Data Analytics – Specialty certification. Everything from self-paced, digital course and hands-on labs, to in-person classroom sessions led by an AWS instructor, are available to you. Check out the AWS Data Analytics Ramp-Up Guide to identify the courses and resources you need to learn how to design, build, secure, and maintain analytics solutions, and to prepare for the exam. And of course, you’ll want to utilize the Official Practice Question Sets. These 20-question sets, developed by AWS, demonstrate the style of our certification exams. These exam-style questions include detailed feedback and recommended resources to help you prepare for your exam.
Workshops and hands-on practice
If you’re looking to get hands-on, check out these self-paced workshops created by AWS Solutions Architects. Each workshop allows you to explore and integrate multiple AWS services to solve a common use case. You’ll learn how data flows from ingestion to visualization. Following are our recommendations:
- If you haven’t used many AWS analytics services, you may want to check out Analytics on AWS, which provides a 200-level foundation for common analytics services you might use such as Amazon Kinesis Data Streams, Amazon S3, AWS Glue, and Amazon QuickSight.
- If you’re working on ingesting data in real- or near-real time and performing analytics on the data or video, try this workshop on Streaming Analytics.
- If you’re a video game enthusiast and curious to learn how analytics and metrics are run without having to provision servers, the Serverless Analytics for Games might be of interest.
Another resource you may consider are the 100+ AWS Builder Labs available in AWS Skill Builder, our digital learning center. AWS Builder Labs are hands-on guided exercises to develop practical skills for common cloud scenarios. You receive a sandbox AWS account for the duration of the lab. There is no need for you to use your own AWS account and risk accruing unwanted charges. Next, we provide you with step-by-step instructions to go through a typical cloud scenario. Builder Labs are available as part of the AWS Skill Builder subscription.
If you would prefer a live workshop led by a specialist Solutions Architect, in person or virtually, you’ll want to get involved in an AWS Immersion Day. These hands-on training events give learners a real-world business scenario they need to solve.
To supplement the aforementioned training, we recommend reading through the Frequently Asked Questions section for all relevant AWS analytics services. They provide detailed insight into potential use-cases, differentiating aspects of the service, as well as pricing information.
As you prepare to take any of the AWS Certification exams, but certainly a specialty certification, take the time to read AWS whitepapers related to the business use cases for the domain certification you’re pursuing. These whitepapers help candidates understand the best practices to use AWS services.
In addition to the plethora of AWS-developed content available to prepare for the exam, there are also quite third-party training resources you may wish to consider. It can be helpful to diversify your study sources as not everyone has the same learning style. If you prefer to learn by watching, we recommend Stephan Maarek’s course on Udemy.
Lastly, if you want to access a larger bank of practice questions, we highly recommend Tutorials Dojo. These questions help test knowledge and illuminate any existing knowledge gaps. These practice question sets will help you get a general sense of the exam style and timing constraints.
Earning your AWS Certified Data Analytics – Specialty certification is a tremendous professional achievement and validates your expertise in using AWS data lakes and analytics services to get insights from data. This industry-recognized credential helps organizations identify and develop talent with critical skills for implementing cloud initiatives – and helps you stand out from the crowd. This certification is helpful to a number of roles and career paths including Data Engineer or a Business Intelligence Engineer, as well as providing you with the specialized expertise to better serve your customers in a variety of IT and cloud roles.
After you’ve earned your data analytics certification, you may wish to pursue building your skills and expertise in machine learning. Since AI/ML has everything to do with data, your work to prepare for the data analytics certification provides a lot of the requisite knowledge for the AWS Certified Machine Learning – Specialty certification.
We wish you all the best in your data analytics learning journey. You’re on the right path!
Finally, consider reading the following blogs for other learner journey stories.