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2. Data Analytics Fundamentals Digital Course by AWS Training
This is a digital training that is self-paced and allows candidates to learn more about planning data analysis solutions & processes. This course walks individuals through the five subjects of the AWS Certified Data Analytics exam, covering basic architecture, potential use cases, and value prepositions, among the rest. It provides detailed information about the AWS services and will the most beneficial for data scientists, data analysts, and data architects who want to enhance their skills in AWS solutions and their implementation. Some of the skills one will master during this program include the following:
- Analyzing how Amazon EMR, Amazon Redshift, and AWS Glue work to process, transform, and cleanse data in data analysis solutions
- Explain AWS services and their work to visualize data
- Analyzing the characteristics of the storage system for source data
- The use of Amazon Kinesis for processing streaming data
- Discovering different concepts of data schemas and defining how data and information is stored in the metastores
- Understanding different ways used to analyze data and make reports with Amazon Athena and Amazon QuickSight tools
- Knowledge of the types of data such as structured, unstructured, and semi-structured
- Classifying the characteristics of data analysis solutions
It is recommended to take this course after experiencing database concepts. The applicant should have a basic understanding of data storage, analytics, and processing. Sessions are offered in Japanese, Portuguese, Spanish, Indonesian, Thai, Vietnamese, Korean, Simplified Chinese, and English.
You can read the AWS Certified Data Analytics Specialty Exam Requirements
There is no prerequisites for AWS Certified Data Analytics - Specialty exam.
Exam Topics
As for Amazon DAS-C01, the vendor provides the learners with the guide that includes the detailed information about all its domains. All in all, the topics covered in the exam content are as follows:
- Security
The questions of the last objective are dedicated to validating the individuals’ understanding of selecting the appropriate authorization and authentication mechanisms, applying data compliance & governance controls, and applying data encryption & protection techniques.
- Collection
The first part requires that the candidates demonstrate their expertise in determining the operational characteristics of features of the collection system, selecting a collection system that addresses the main properties of data, such as compression, format, and order, as well as selecting a collection system, which handles the source, volume, and frequency of data.
- Analysis and Visualization
This topic is all about the students’ ability to demonstrate a wide range of technical tasks related to visualization and analysis of data, including selecting the right data visualization & data analysis solutions for a specific scenario, as well as determining the operational features of visualization and analysis solution.
- Storage and Data Management
This domain evaluates the professionals’ skills in determining the operational characteristics of the given storage solution for analytics, defining a data lifecycle based on the business requirements & usage patterns, determining an appropriate system for managing Metadata and cataloging data, as well as selecting the appropriate data layout, format, structure & schema, and determining data access & retrieval patterns.
- Processing
In the framework of this subject area, the test takers have to perform their knowledge and skills in determining the proper data processing solution requirements, operationalizing & automating a data processing solution, designing a solution for preparing and transforming data for analysis, and more.
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