HOT DAS-C01 Exam Passing Score - High Pass-Rate Amazon Latest DAS-C01 Exam Question: AWS Certified Data Analytics - Specialty (DAS-C01) Exam

Category: Blog

DAS-C01 Exam Passing Score, Latest DAS-C01 Exam Question, DAS-C01 Latest Exam Labs, Study DAS-C01 Material, Passing DAS-C01 Score

The AWS Certified Data Analytics - Specialty (DAS-C01) Exam (DAS-C01) PDF dumps are suitable for smartphones, tablets, and laptops as well. So you can study actual AWS Certified Data Analytics - Specialty (DAS-C01) Exam (DAS-C01) questions in PDF easily anywhere. ValidVCE updates AWS Certified Data Analytics - Specialty (DAS-C01) Exam (DAS-C01) PDF dumps timely as per adjustments in the content of the actual Amazon DAS-C01 exam. In the Desktop DAS-C01 practice exam software version of Amazon DAS-C01 Practice Test is updated and real. The software is useable on Windows-based computers and laptops. There is a demo of the AWS Certified Data Analytics - Specialty (DAS-C01) Exam (DAS-C01) practice exam which is totally free. AWS Certified Data Analytics - Specialty (DAS-C01) Exam (DAS-C01) practice test is very customizable and you can adjust its time and number of questions.

Amazon AWS-Certified-Data-Analytics-Specialty (AWS Certified Data Analytics - Specialty (DAS-C01)) Certification Exam is designed to test the skills and knowledge necessary to work with data analytics on the Amazon Web Services (AWS) platform. AWS Certified Data Analytics - Specialty (DAS-C01) Exam certification is for individuals who want to demonstrate their expertise in designing, building, and maintaining secure, scalable, and cost-effective data analytics solutions using AWS services.

The AWS Certified Data Analytics – Specialty certification exam covers a range of topics including data collection, processing, analysis, visualization, and interpretation. DAS-C01 exam also covers AWS services such as Amazon Kinesis, Amazon Redshift, Amazon Athena, and Amazon QuickSight. Candidates for the exam should have a deep understanding of AWS data analytics services and how to use them to build effective solutions.

>> DAS-C01 Exam Passing Score <<

Latest Amazon DAS-C01 Exam Question - DAS-C01 Latest Exam Labs

Our experts who compiled the DAS-C01 practice materials are assiduously over so many years in this filed. They add the new questions into the DAS-C01 study guide once the updates come in the market, so they recompose the contents according to the syllabus and the trend being relentless in recent years. With so accurate information of our DAS-C01 learning questions, we can confirm your success by your first attempt.

The AWS Certified Data Analytics - Specialty certification exam is a valuable credential for professionals looking to advance their careers in data analytics. AWS Certified Data Analytics - Specialty (DAS-C01) Exam certification demonstrates to employers that candidates have the skills and knowledge needed to design, build, and maintain analytics solutions using AWS services. With the growing demand for data analytics professionals, the AWS Certified Data Analytics - Specialty certification is an excellent way for individuals to stand out in the job market and advance their careers.

Amazon AWS Certified Data Analytics - Specialty (DAS-C01) Exam Sample Questions (Q137-Q142):

NEW QUESTION # 137
A technology company is creating a dashboard that will visualize and analyze time-sensitive data. The data will come in through Amazon Kinesis Data Firehose with the butter interval set to 60 seconds. The dashboard must support near-real-time data.
Which visualization solution will meet these requirements?

  • A. Select Amazon Redshift as the endpoint for Kinesis Data Firehose. Connect Amazon QuickSight with SPICE to Amazon Redshift to create the desired analyses and visualizations.
  • B. Select Amazon S3 as the endpoint for Kinesis Data Firehose. Use AWS Glue to catalog the data and Amazon Athena to query it. Connect Amazon QuickSight with SPICE to Athena to create the desired analyses and visualizations.
  • C. Select Amazon Elasticsearch Service (Amazon ES) as the endpoint for Kinesis Data Firehose. Set up a Kibana dashboard using the data in Amazon ES with the desired analyses and visualizations.
  • D. Select Amazon S3 as the endpoint for Kinesis Data Firehose. Read data into an Amazon SageMaker Jupyter notebook and carry out the desired analyses and visualizations.

Answer: C


NEW QUESTION # 138
A company's marketing team has asked for help in identifying a high performing long-term storage service for their data based on the following requirements:
* The data size is approximately 32 TB uncompressed.
* There is a low volume of single-row inserts each day.
* There is a high volume of aggregation queries each day.
* Multiple complex joins are performed.
* The queries typically involve a small subset of the columns in a table.
Which storage service will provide the MOST performant solution?

  • A. Amazon Aurora MySQL
  • B. Amazon Redshift
  • C. Amazon Neptune
  • D. Amazon Elasticsearch

Answer: B


NEW QUESTION # 139
An online retailer is rebuilding its inventory management system and inventory reordering system to automatically reorder products by using Amazon Kinesis Data Streams. The inventory management system uses the Kinesis Producer Library (KPL) to publish data to a stream. The inventory reordering system uses the Kinesis Client Library (KCL) to consume data from the stream. The stream has been configured to scale as needed. Just before production deployment, the retailer discovers that the inventory reordering system is receiving duplicated data.
Which factors could be causing the duplicated data? (Choose two.)

  • A. The max_records configuration property was set to a number that is too high.
  • B. The stream's value for the IteratorAgeMilliseconds metric is too high.
  • C. The AggregationEnabled configuration property was set to true.
  • D. There was a change in the number of shards, record processors, or both.
  • E. The producer has a network-related timeout.

Answer: B,C


NEW QUESTION # 140
A large telecommunications company is planning to set up a data catalog and metadata management for multiple data sources running on AWS. The catalog will be used to maintain the metadata of all the objects stored in the data stores. The data stores are composed of structured sources like Amazon RDS and Amazon Redshift, and semistructured sources like JSON and XML files stored in Amazon S3. The catalog must be updated on a regular basis, be able to detect the changes to object metadata, and require the least possible administration.
Which solution meets these requirements?

  • A. Use the AWS Glue Data Catalog as the central metadata repository. Extract the schema for RDS and Amazon Redshift sources and build the Data Catalog. Use AWS crawlers for data stored in Amazon S3 to infer the schema and automatically update the Data Catalog.
  • B. Use the AWS Glue Data Catalog as the central metadata repository. Use AWS Glue crawlers to connect to multiple data stores and update the Data Catalog with metadata changes. Schedule the crawlers periodically to update the metadata catalog.
  • C. Use Amazon DynamoDB as the data catalog. Create AWS Lambda functions that will connect and gather the metadata information from multiple sources and update the DynamoDB catalog. Schedule the Lambda functions periodically.
  • D. Use Amazon Aurora as the data catalog. Create AWS Lambda functions that will connect and gather the metadata information from multiple sources and update the data catalog in Aurora. Schedule the Lambda functions periodically.

Answer: A


NEW QUESTION # 141
A company wants to optimize the cost of its data and analytics platform. The company is ingesting a number of .csv and JSON files in Amazon S3 from various data sources. Incoming data is expected to be 50 GB each day. The company is using Amazon Athena to query the raw data in Amazon S3 directly. Most queries aggregate data from the past 12 months, and data that is older than 5 years is infrequently queried. The typical query scans about 500 MB of data and is expected to return results in less than 1 minute. The raw data must be retained indefinitely for compliance requirements.
Which solution meets the company's requirements?

  • A. Use an AWS Glue ETL job to compress, partition, and convert the data into a columnar data format. Use Athena to query the processed dataset. Configure a lifecycle policy to move the processed data into the Amazon S3 Standard-Infrequent Access (S3 Standard-IA) storage class 5 years after the object was last accessed. Configure a second lifecycle policy to move the raw data into Amazon S3 Glacier for long-term archival 7 days after the last date the object was accessed.
  • B. Use an AWS Glue ETL job to compress, partition, and convert the data into a columnar data format. Use Athena to query the processed dataset. Configure a lifecycle policy to move the processed data into the Amazon S3 Standard-Infrequent Access (S3 Standard-IA) storage class 5 years after object creation.
    Configure a second lifecycle policy to move the raw data into Amazon S3 Glacier for long-term archival 7 days after object creation.
  • C. Use an AWS Glue ETL job to partition and convert the data into a row-based data format. Use Athena to query the processed dataset. Configure a lifecycle policy to move the data into the Amazon S3 Standard- Infrequent Access (S3 Standard-IA) storage class 5 years after the object was last accessed.
    Configure a second lifecycle policy to move the raw data into Amazon S3 Glacier for long-term archival 7 days after the last date the object was accessed.
  • D. Use an AWS Glue ETL job to partition and convert the data into a row-based data format. Use Athena to query the processed dataset. Configure a lifecycle policy to move the data into the Amazon S3 Standard- Infrequent Access (S3 Standard-IA) storage class 5 years after object creation. Configure a second lifecycle policy to move the raw data into Amazon S3 Glacier for long-term archival 7 days after object creation.

Answer: A


NEW QUESTION # 142
......

Latest DAS-C01 Exam Question: https://www.validvce.com/DAS-C01-exam-collection.html

123456789101112131415

Leave a Reply

Your email address will not be published. Required fields are marked *