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The AWS Certified Big Data Specialty exam is one of the toughest exams and it requires you a lot of hands-on experience. It is advisable to have prior knowledge of Big Data technologies on AWS. The more experience you have, the more it is beneficial for you, Major challenging things which you can find in exam is about different scenario based questions, you must have strong understanding of Big Data.
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AWS Certified Big Data - Specialty Exam Overview
AWS Certified Big Data - Specialty Exam Overview:
- Registration Fee: 300 USD
- Format: Multiple choice, multiple answer
- Length of Examination: 170 minutes
- Passing Score: 75-80%
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AWS Certified Big Data - Specialty Exam Dumps Provided Study Notes
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- Kinesis Firehose and Kinesis Stream: Kinesis firehose and Kinesis stream are big data terms associated with streaming real time data to destinations such as S3, ES and spunk. You would require to know the importance of Kinesis and combining it with Lambda. Also learn where the Firehose will unload the content. Also understand why kinesis ingestion is better. Learn features offered by KCL and KPL. Also understand when to use them to send/receive data.
- S3: Amazon S3 is storage for internet: It is a simple web service interface which is used to store and retrieve data anywhere anytime. You would require to know how to use S3 buckets, when to use S3 standards and S3 glacier.
- DynamoDB: DymanoDB is a NoSQL database services for all application that need consistent, single digit millisecond latency at any scale. Study the right use case for DymanoDB. How to design LSI and GSI. You might get asked about key optimization.
- Quicksight: It is a fast cloud-powered business analytics service. You may be asked a question on virtual representation with Quicksight.
- Redshift: AWS redshift is a fast, fully managed data warehouse which helps you analyze your data using SQL and BI. You will need to know how to load data using Redshift. You will need to understand the overall architecture. Leader, node slices, compute node. Redshift is an important topic and you would require to know the importance of the COPY command. Also to migrate data using UNLOAD command. Tuning performance use right sort key. At least one question on loading data in Redshift is asked. For this you should know what slices are and instances.
- IoT: The questions will be asked mixed with topics like as DynamoDB and Kinesis Stream. You will require knowledge of IoT rules, Device Registry, Device Gateway, Device Shadow, etc.
- Machine Learning: Knowledge of which types of models are by AWS Machine learning. Also understand when to select right model for specific business requirements and scenarios.
- Security: IAM roles, data encryption for S3, Redshift and DynamoDB, HSM.
- Data Pipeline: Some questions will be asked on Data pipeline, Data Pipeline and Lambda and when to us it. Questions on backup, restore data into other AWS regions.
There is no doubt that in the future information society, knowledge and skills will be a major driver for economic growth and one of the major contributors to the sustainable development of the information industry. And getting the related AWS Certified Big Data - Specialty certification in your field will be the most powerful way for you to show your professional knowledge and skills. However, it is not easy for the majority of candidates to prepare for the exam in order to pass it, if you are one of the candidates who are worrying about the exam now, congratulations, there is a panacea for you--our AWS-Certified-Big-Data-Specialty study tool. We can assure you that you can pass the exam as well as getting the related certification in a breeze with the guidance of our AWS Certified Big Data - Specialty test torrent, now I would like to introduce some details about our AWS-Certified-Big-Data-Specialty guide torrent for you.
AWS Certified Big Data - Specialty Dumps will include below mentioned topics with Exam focused percentage
AWS Certified Big Data - Specialty Dumps will include below mentioned topics with Exam focused percentage:
- Processing 17%
- Collection 17%
- Storage 17%
- Analysis 17%
- Visualization 12%
- Data Security 20%

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