Target Audience
The potential candidates for the Amazon AWS Certified Data Analytics – Specialty exam are those individuals who are performing the Data Analytics roles. The test is generally targeted at the applicants who are working in different positions, such as a Solutions Architect, a Data Platform Engineer, a Data Scientist, as well as a Data Architect and a Data Analyst.
Simulate the real exam
We provide different versions of DAS-C01日本語 practice exam materials for our customers, among which the software version can stimulate the real exam for you but it only can be used in the windows operation system. It tries to simulate the DAS-C01日本語 best questions for our customers to learn and test at the same time and it has been proved to be good environment for IT workers to find deficiencies of their knowledge in the course of stimulation.
After purchase, Instant Download: Upon successful payment, Our systems will automatically send the product you have purchased to your mailbox by email. (If not received within 12 hours, please contact us. Note: don't forget to check your spam.)
AWS Data Analytics Specialty Exam Syllabus Topics:
| Section | Objectives |
|---|---|
Collection - 18% | |
| Determine the operational characteristics of the collection system | - Evaluate that the data loss is within tolerance limits in the event of failures - Evaluate costs associated with data acquisition, transfer, and provisioning from various sources into the collection system (e.g., networking, bandwidth, ETL/data migration costs) - Assess the failure scenarios that the collection system may undergo, and take remediation actions based on impact - Determine data persistence at various points of data capture - Identify the latency characteristics of the collection system |
| Select a collection system that handles the frequency, volume, and the source of data | - Describe and characterize the volume and flow characteristics of incoming data (streaming, transactional, batch) - Match flow characteristics of data to potential solutions - Assess the tradeoffs between various ingestion services taking into account scalability, cost, fault tolerance, latency, etc. - Explain the throughput capability of a variety of different types of data collection and identify bottlenecks - Choose a collection solution that satisfies connectivity constraints of the source data system |
| Select a collection system that addresses the key properties of data, such as order, format, and compression | - Describe how to capture data changes at the source - Discuss data structure and format, compression applied, and encryption requirements - Distinguish the impact of out-of-order delivery of data, duplicate delivery of data, and the tradeoffs between at-most-once, exactly-once, and at-least-once processing - Describe how to transform and filter data during the collection process |
Storage and Data Management - 22% | |
| Determine the operational characteristics of the storage solution for analytics | - Determine the appropriate storage service(s) on the basis of cost vs. performance - Understand the durability, reliability, and latency characteristics of the storage solution based on requirements - Determine the requirements of a system for strong vs. eventual consistency of the storage system - Determine the appropriate storage solution to address data freshness requirements |
| Determine data access and retrieval patterns | - Determine the appropriate storage solution based on update patterns (e.g., bulk, transactional, micro batching) - Determine the appropriate storage solution based on access patterns (e.g., sequential vs. random access, continuous usage vs.ad hoc) - Determine the appropriate storage solution to address change characteristics of data (appendonly changes vs. updates) - Determine the appropriate storage solution for long-term storage vs. transient storage - Determine the appropriate storage solution for structured vs. semi-structured data - Determine the appropriate storage solution to address query latency requirements |
| Select appropriate data layout, schema, structure, and format | - Determine appropriate mechanisms to address schema evolution requirements - Select the storage format for the task - Select the compression/encoding strategies for the chosen storage format - Select the data sorting and distribution strategies and the storage layout for efficient data access - Explain the cost and performance implications of different data distributions, layouts, and formats (e.g., size and number of files) - Implement data formatting and partitioning schemes for data-optimized analysis |
| Define data lifecycle based on usage patterns and business requirements | - Determine the strategy to address data lifecycle requirements - Apply the lifecycle and data retention policies to different storage solutions |
| Determine the appropriate system for cataloging data and managing metadata | - Evaluate mechanisms for discovery of new and updated data sources - Evaluate mechanisms for creating and updating data catalogs and metadata - Explain mechanisms for searching and retrieving data catalogs and metadata - Explain mechanisms for tagging and classifying data |
Processing - 24% | |
| Determine appropriate data processing solution requirements | - Understand data preparation and usage requirements - Understand different types of data sources and targets - Evaluate performance and orchestration needs - Evaluate appropriate services for cost, scalability, and availability |
| Design a solution for transforming and preparing data for analysis | - Apply appropriate ETL/ELT techniques for batch and real-time workloads - Implement failover, scaling, and replication mechanisms - Implement techniques to address concurrency needs - Implement techniques to improve cost-optimization efficiencies - Apply orchestration workflows - Aggregate and enrich data for downstream consumption |
| Automate and operationalize data processing solutions | - Implement automated techniques for repeatable workflows - Apply methods to identify and recover from processing failures - Deploy logging and monitoring solutions to enable auditing and traceability |
Analysis and Visualization - 18% | |
| Determine the operational characteristics of the analysis and visualization solution | - Determine costs associated with analysis and visualization - Determine scalability associated with analysis - Determine failover recovery and fault tolerance within the RPO/RTO - Determine the availability characteristics of an analysis tool - Evaluate dynamic, interactive, and static presentations of data - Translate performance requirements to an appropriate visualization approach (pre-compute and consume static data vs. consume dynamic data) |
| Select the appropriate data analysis solution for a given scenario | - Evaluate and compare analysis solutions - Select the right type of analysis based on the customer use case (streaming, interactive, collaborative, operational) |
| Select the appropriate data visualization solution for a given scenario | - Evaluate output capabilities for a given analysis solution (metrics, KPIs, tabular, API) - Choose the appropriate method for data delivery (e.g., web, mobile, email, collaborative notebooks) - Choose and define the appropriate data refresh schedule - Choose appropriate tools for different data freshness requirements (e.g., Amazon Elasticsearch Service vs. Amazon QuickSight vs. Amazon EMR notebooks) - Understand the capabilities of visualization tools for interactive use cases (e.g., drill down, drill through and pivot) - Implement the appropriate data access mechanism (e.g., in memory vs. direct access) - Implement an integrated solution from multiple heterogeneous data sources |
Security - 18% | |
| Select appropriate authentication and authorization mechanisms | - Implement appropriate authentication methods (e.g., federated access, SSO, IAM) - Implement appropriate authorization methods (e.g., policies, ACL, table/column level permissions) - Implement appropriate access control mechanisms (e.g., security groups, role-based control) |
| Apply data protection and encryption techniques | - Determine data encryption and masking needs - Apply different encryption approaches (server-side encryption, client-side encryption, AWS KMS, AWS CloudHSM) - Implement at-rest and in-transit encryption mechanisms - Implement data obfuscation and masking techniques - Apply basic principles of key rotation and secrets management |
| Apply data governance and compliance controls | - Determine data governance and compliance requirements - Understand and configure access and audit logging across data analytics services - Implement appropriate controls to meet compliance requirements |
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
There is no doubt that the IT examination plays an essential role in the IT field. On the one hand, there is no denying that the DAS-C01日本語 practice exam materials provides us with a convenient and efficient way to measure IT workers' knowledge and ability(DAS-C01日本語 best questions). On the other hand, up to now, no other methods have been discovered to replace the examination. That is to say, the IT examination is still regarded as the only reliable and feasible method which we can take (DAS-C01日本語 certification training), and other methods are too time- consuming and therefore they are infeasible, thus it is inevitable for IT workers to take part in the IT exam. However, how to pass the Amazon DAS-C01日本語 exam has become a big challenge for many people and if you are one of those who are worried, congratulations, you have clicked into the right place--DAS-C01日本語 practice exam materials. Our company is committed to help you pass exam and get the IT certification easily. Our company has carried out cooperation with a lot of top IT experts in many countries to compile the DAS-C01日本語 best questions for IT workers and our exam preparation are famous for their high quality and favorable prices. The shining points of our DAS-C01日本語 certification training files are as follows.
Fast delivery in 5 to 10 minutes after payment
Our company knows that time is precious especially for those who are preparing for Amazon DAS-C01日本語 exam, just like the old saying goes "Time flies like an arrow, and time lost never returns." We have tried our best to provide our customers the fastest delivery. We can ensure you that you will receive our DAS-C01日本語 practice exam materials within 5 to 10 minutes after payment, this marks the fastest delivery speed in this field. Therefore, you will have more time to prepare for the DAS-C01日本語 actual exam. Our operation system will send the DAS-C01日本語 best questions to the e-mail address you used for payment, and all you need to do is just waiting for a while then check your mailbox.
Only need to practice for 20 to 30 hours
You will get to know the valuable exam tips and the latest question types in our DAS-C01日本語 certification training files, and there are special explanations for some difficult questions, which can help you to have a better understanding of the difficult questions. All of the questions we listed in our DAS-C01日本語 practice exam materials are the key points for the IT exam, and there is no doubt that you can practice all of DAS-C01日本語 best questions within 20 to 30 hours, even though the time you spend on it is very short, however the contents you have practiced are the quintessence for the IT exam. And of course, if you still have any misgivings, you can practice our DAS-C01日本語 certification training files again and again, which may help you to get the highest score in the IT exam.
