AWS-certified professionals are a must-have for professionals and individuals who want to succeed in their industry. Being certified is the key to a job at a high-level position globally. AWS Data Analytics Specialists require experience and attention to start a career. Due to the increased demand for AWS certifications the level of competition has also increased. There will be many competitors for this position, so you need to stick to a clear roadmap to stay ahead.
To stand out in this highly competitive job market, it is important to have advanced-level certification. AWS cloud services are a rapidly-growing industry, even in 2020, widely regarded as one the most tragic years in human history. AWS certification is a must if you are looking to become a Data Analytics Specialist. We will walk you through each step of getting the job you want. Before we get to the roadmap, take a look at the overview of data analysts, including their responsibilities.
Who are AWS Data Analysts?
AWS data analysts are responsible to bridge the gap between data analysis and decision-making. Amazon data analysts have many responsibilities, including data analysis, dashboard/report design, metric definitions, and reviews. They also create data collection, compilation, analysis, reporting systems, and other responsibilities. Data analyst positions can vary depending on what kind of data they are dealing with, the project they are working on, and the team they have been assigned. Data analysts at Amazon work cross-functionally alongside engineering, data science, marketing teams to provide data-driven insights for research and business sectors. Depending on the team, this function could include data processing, analysis and reporting, or a more technical role such as data collection.
Basic Requirements
First, a bachelor’s or masters degree in finance or economics, business, engineering, maths, statistics, computer science or operations research or a related discipline (Ph.D. recommended).
Second, scripting, querying and data warehousing technologies such as Linux, R SAS, and/or SQL are preferred. A good programming background in languages like Java, R, and Python is a plus.
Third, hands-on experience with the processing, optimization and analysis of large data sets as well as accessing relational databases.
Finally, experience in -Firstly, identifying measures and KPIs and collecting data, experimenting and presenting decks and dashboards, as well as scorecards and scorecards, are all part of this process.
Secondly, Tableau and Quicksight are examples of business intelligence systems and self-service reporting systems.

We will now move on to the next section. Here we will begin our preparation and the journey to a job role.
Pathway to becoming an AWS Data Analytics Specialist
To be an AWS Data Analytics Specialist, the first and most important thing is to pass the certification. Let’s now get a better understanding of the AWS exam.
Step 1 – Register for the AWS Data Analytics Specialty Exam
The AWS Certified Data Analytics Specialty is for you if you have the knowledge and skills to work with AWS services to build, construct, protect and maintain analytics systems. It is highly recommended that you have the following items in order to pass this exam:
First, five years of experience with data analytics technologies.
Second, two years of practical experience and competence in designing, building and securing analytics applications using AWS services.
Finally, the ability to: Firstly, specify AWS data analytics services, and understand the process of integrating with one another
Secondly, we will describe the AWS data analytics process that fits in the data lifecycle of storage, processing, processing, visualization.

Step 2 – Understanding Exam Objectives
It is recommended that each topic for the AWS exam be reviewed. The topics are divided into sections and subsections. It will help you prepare for the exam by understanding the principles behind the topics. These are the most important topics:
Deciding the operational characteristics for the collection system
Choose a collection system that can handle frequency, volume, as well as source data
Choose a data collection method that considers essential data qualities such as order, format, compression
Data Management and Storage
Deciding the operational characteristics for the storage solution to store analytics
Deciding data access/retrieval patterns
Selecting the right data layout, schema, structure, or format
Specificating data lifecycle based on business requirements and usage patterns
Deciding the right system for managing metadata and cataloging data
Deciding suitable data processing solution requirements
Planning solution to convert and prepare data for analysis
Data processing solutions that automate and operate effectively
Analysis and Visualization
Deciding the operational characteristics for the analysis and visualization solution
Selecting the right data analysis solution for a given situation
Selecting the right data visualization solution for a given situation
Selecting the right authentication and authorization mechanism
Implementing encryption and data protection methods
Implementing data governance, compliance controls
Step 3 – Prepare for AWS Recommended Training
AWS offers many courses to help you develop and improve your technical skills. You will be able cover the man with the help of an expert