AWS Certified Data Analytics Study Guide: Specialty (DAS-C01) Exam

✍ Scribed by Asif Abbasi

• Publisher: Sybex
• Year: 2020
• Tongue: English
• Leaves: 405
• Edition: 1
• Category: Library

✦ Synopsis

Move your career forward with AWS certification! Prepare for the AWS Certified Data Analytics Specialty Exam with this thorough study guide

This comprehensive study guide will help assess your technical skills and prepare for the updated AWS Certified Data Analytics exam. Earning this AWS certification will confirm your expertise in designing and implementing AWS services to derive value from data. The AWS Certified Data Analytics Study Guide: Specialty (DAS-C01) Exam is designed for business analysts and IT professionals who perform complex Big Data analyses.

This AWS Specialty Exam guide gets you ready for certification testing with expert content, real-world knowledge, key exam concepts, and topic reviews. Gain confidence by studying the subject areas and working through the practice questions. Big data concepts covered in the guide include:
• Collection
• Storage
• Processing
• Analysis
• Visualization
• Data security

AWS certifications allow professionals to demonstrate skills related to leading Amazon Web Services technology. The AWS Certified Data Analytics Specialty (DAS-C01) Exam specifically evaluates your ability to design and maintain Big Data, leverage tools to automate data analysis, and implement AWS Big Data services according to architectural best practices. An exam study guide can help you feel more prepared about taking an AWS certification test and advancing your professional career. In addition to the guide’s content, you’ll have access to an online learning environment and test bank that offers practice exams, a glossary, and electronic flashcards.

✦ Subjects

Amazon Web Services; Data Analysis; Big Data; Data Visualization; Apache Hive; Apache Pig; Graph Data Model; Apache Hadoop; Elasticsearch; Data Lake; AWS Redshift; AWS Athena; AWS Glacier; AWS Simple Storage Service; AWS Direct Connect; AWS Kinesis Data Streams; AWS Data Pipeline; AWS Glue; AWS Kinesis Analytics; Data Security; AWS IoT; AWS DocumentDB; AWS DynamoDB; AWS Neptune; AWS QuickSight