Exam AWS Certified Data Analytics - Specialty topic 1 question 51 discussion

It is A. QuickSight does not support S3 files with parquet format, Athena does it. For visualization is better a graph than a pivot table. https://docs.aws.amazon.com/athena/latest/ug/when-should-i-use-ate.html https://docs.aws.amazon.com/quicksight/latest/user/supported-data-sources.html

Agree wih C. Thoughts?

A or C? For me both are valid - QuickSight does not support S3 files with parquet format. - AWS says here https://docs.aws.amazon.com/quicksight/latest/user/pivot-table.html "Heat maps and pivot tables display data in a similar tabular fashion. Use a heat map if you want to identify trends and outliers, because the use of color makes these easier to spot. Use a pivot table if you want to analyze data on the visual."

Ans Is C . Athena as the data is in Parquet format and Pivot table as it was to identify sub-organization is the strongest performer in each country whereas heat map will provide only correlation

B: I passed the test

Answer is A Since Parquet is mentioned then Athena. Visuals means heat map, Pivot table is just a table with Data

Answer is A Since Parquet is mentioned then Athena. Visuals means heat map, Pivot table is just a table with Data

The correct answer is A. Here’s why: A is correct because Amazon QuickSight can be used with Amazon Athena as the data source to visualize sales data stored in Amazon S3 in Parquet format. Heat maps can be used as the visual type to quickly identify which sub-organization is the strongest performer in each country. Heat maps are a great way to visualize data that is organized in a grid format, such as sales data. C is incorrect because pivot tables are not the best visual type to use for this scenario. Pivot tables are great for summarizing and analyzing large amounts of data, but they are not the best way to visualize data.

Correct answer is A as Quicksight can use Athena as data source to query the data in S3. Heat Maps would provide the required visual representation. Heat maps and pivot tables display data in a similar tabular fashion. Use a heat map if you want to identify trends and outliers, because the use of color makes these easier to spot. Use a pivot table if you want to analyze data on the visual. Option C is wrong as Heat Map would provide the required visual and would be preferred over Pivot tables as there is not need to analyze the data. Options B & D are wrong as Quicksight supports S3 as a data source, however it does not work directly with parquet file format.

Quickly identification is possible by HeatMap color coding feature. Pivot table is unnecessary here. Athena is required as data is stored in Parquet format.

c, heat maps are for correlation (

heat maps are for correlation (P.S.: heat maps do not use a world map) -> Pivot tables is correct here. quick-sight cannot directly query parquet files.

Selected Answer: A

Ans is B. Heat map allows one simple chart to show the pattern for the whole thing easily. QuickSight can use S3 as data source. Creating a dataset using Amazon S3 files - Amazon QuickSight https://docs.aws.amazon.com/quicksight/latest/user/create-a-data-set-s3.html

Ans is C. Heat map is to show co-relation and identify outliers. Here the requirement is very straightforward which is to identify best performer in each region. Hence Pivot table.

My Answer is A

swiftly determine which sub-organization is the best performance in each country C: is the answer , because (in each country)you should use pivot table