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Answer: Utilize Amazon Athena for ad-hoc querying and Amazon QuickSight for KPI visualization., Implement AWS Lake Formation blueprints for data ingestion into a data lake, processed by AWS Glue into Amazon S3 in Parquet format.
The best combination that meets the company's requirements with the least operational overhead is A and E. Using Amazon Athena allows teams to run ad-hoc queries directly on data stored in Amazon S3 without the need to manage any infrastructure, minimizing operational overhead. Amazon QuickSight can then be used to create dashboards for KPIs from the query results. In addition, AWS Lake Formation and AWS Glue together streamline the data ingestion, cataloging, and transformation processes. Lake Formation helps to set up the data lake quickly, and AWS Glue can crawl, extract, and load data into Amazon S3 in an optimized format like Apache Parquet, making the data ready for analysis in Athena or other services.
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A company generates batch and live stream data from various sources requiring consolidation for analytics. How can they achieve this with minimal operational overhead while enabling one-time queries and KPI dashboards?
A
Utilize Amazon Athena for ad-hoc querying and Amazon QuickSight for KPI visualization.
B
Employ Amazon Kinesis Data Analytics for one-time queries with Amazon QuickSight for dashboards.
C
Develop AWS Lambda functions for data transfer to Amazon Redshift from databases.
D
Leverage AWS Glue to transform data to JSON and load into Amazon OpenSearch Service clusters.
E
Implement AWS Lake Formation blueprints for data ingestion into a data lake, processed by AWS Glue into Amazon S3 in Parquet format.
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