How to pass the AWS Certified Data Analytics Specialty Exam Blog
Every company is looking for data analysts to manage the increasing amount of data they have. Data analysts are responsible for spotting trends and making forecasts. They also extract information to aid employers in making better business decisions. The role of data analyst is becoming more important due to the many opportunities available in a variety of industries, including finance, marketing, and social media. This article will help you prepare for the AWS Certified Data Analytics Specialty Examination with the most current learning resources.
Organizations can recognize and promote talent with key skills to perform cloud initiatives by obtaining the AWS Certified Data Analytics Specialty Exam credential. An AWS Certified Data Analytics – Specialty credential demonstrates expertise in using the AWS data lakes, analytics services, and data mining techniques to extract value from data. The exam also assesses candidates’ knowledge and understanding of how to create, operate, and defend data analytics solutions on AWS. It also examines the candidate’s ability to use several AWS-related data analytics services.
It’s time for you to gain some knowledge and understanding.
Recommendations
AWS Certified Data Analytics – Specialty is for those who have experience using AWS services to create, design, secure and manage analytics solutions. We recommend that you have the following:
First, at least 5 years of experience with data analytics technologies
The candidate must also have at least 2 years of experience in the AWS.
Finally, knowledge of AWS services for building and designing, securing, as well as sustaining analytics solutions.
Specifications for Exam
It takes a lot of preparation to get the exam construction format. It is a draft of the exam format that encourages candidates to be prepared for what they will face on exam day. The candidate will be able to adjust their preparations for the exam by becoming familiar with its format and purposes.
The applicant must attempt 65 Multiple Choice and Multi Response Questions. It will take 180 minutes for the candidate to complete. It will cost them $300 USD and can be completed in English, Korean and Japanese. languages. To obtain this credential, they must score passing marks of 75% to 80%.
The most important part is now, the outline of the AWS exam.
Course Structure
The applicant must be familiar with the relevant fields and topics.
Collection
Determining the operational requirements of the collection system
In the event of a failure, ensure that data loss is within acceptable limits
Assess the costs associated with data acquisition, transmission, and provisioning from different sources into the collection system (e.g. bandwidth, ETL/datamigration costs, networking, bandwidth).
Assess the potential failure scenarios for the collection system and take remediation steps based on the impact
Data persistence at different points of data capture
Identify the latency characteristics for the collection system
Selecting a collection that addresses the frequency, volume, as well as source of data
Description and description of the flow characteristics of incoming data (streaming or transactional, batch)
Match data flow to find potential solutions
Analyzing the tradeoffs between different ingestion services, taking into account scalability and cost, fault tolerance, latency etc.
Explain the throughput capability of a variety data collection methods and identify the bottlenecks
Choose a collection solution that meets the connectivity constraints of your source data system
Choose a collection system that addresses key data properties such as format, order, and compression
Describe how to capture data modifications at the source
Discuss data structure, format, compression, and encryption requirements
Differentiate the effects of duplicate delivery of data and out-of-order data delivery. Also, consider the tradeoffs between at least-once, exactly once, and at-least once processing
Describe the process of filtering and transforming data during data collection
Data Management and Storage
Analytical storage solutions operational characteristics
The cost-performance ratio is the deciding factor in choosing the right storage service.
Based on your requirements, you can determine the reliability, durability, latency, and longevity of the storage solution.
Determine the storage system’s requirements for strength and eventual consistency
Choose the right storage solution to meet data freshness requirements
Determining data access and retrieval patterns
Based on the update patterns (e.g. bulk, transactional and micro batching), determine the best storage solution.
Access patterns are important factors in choosing the right storage solution.
Deciding the best storage solution to address data change functions (append-only vs. updates).
Determining the storage solution that will allow for long-term storage or transient storage
Storage solution for structured and semi-structured data
Finding the right storage solution to address query latency requirements
Selecting the right data structure, format, schema, or layout
It is necessary to determine the relevant mechanisms for direct schema evolution.
The storage arrangement that best suits the task
Strategies for compression/encoding the preferred storage format
Effective data access requires you to choose the right data sorting and distribution strategies, and the storage layout
Explaining the production and cost implications of complex data distributions, layouts and formats (e.g. size and number of files).
Data formatting and partitioning for data-optimized analyses