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Understanding useful and specialized parts of AWS Certified Data Analytics - Specialty (DAS-C01) Professional Exam Migration Planning

The accompanying will be dicussed in AMAZON DAS C01 exam dumps:

• COPY command can utilize manifest files to load data
• Learn Redshift Advanced materials like Workload Management, Distribution Style, Sort key
• COPY command enables parallelism, and functions better than multiple COPY commands
• COPY command manages coded data
• Know Redshift Best Practices concerning choice of Distribution style, Sort key, importing/exporting data
• Learn Redshift in detail
• Define suitable data processing solution needs
• Automate and operationalize a data processing solution
• Redshift
• Grasp Redshift Spectrum which enables querying data in S3
• Glue supports Job Bookmark as it helps in tracking data that has been treated during a previous run.
• Learn and grasp Glue as a fully-managed, extract, and load service
• Glue locally supports RDS, and databases on EC2 occurrences
• Elasticsearch
• Compose a solution for changing and preparing data for analysis
• DAS-C01 incorporates Glue in depth. This is a new service as compared to Big Data -Specialty test
• Identify ElasticSearch is a search service that maintains indexing, full text search, faceting etc
• Elasticsearch can be utilised to analysis and assist visualization using Kibana which can be real time
• Glue crawls data and aids in identifying and creating schema in Glue Data Catalog
• Grasp Redshift views to manage access to data

Reference: https://d1.awsstatic.com/training-and-certification/docs-data-analytics-specialty/AWS-Certified-Data-Analytics-Specialty-Exam-Guide_v1.0_08-23-2019_FINAL.pdf

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:

• Classifying the characteristics of data analysis solutions
• Knowledge of the types of data such as structured, unstructured, and semi-structured
• Understanding different ways used to analyze data and make reports with Amazon Athena and Amazon QuickSight tools
• Analyzing how Amazon EMR, Amazon Redshift, and AWS Glue work to process, transform, and cleanse data in data analysis solutions
• Analyzing the characteristics of the storage system for source data
• Discovering different concepts of data schemas and defining how data and information is stored in the metastores
• Explain AWS services and their work to visualize data
• The use of Amazon Kinesis for processing streaming data

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.