HikeHills.com (HH) is an online specialty retailer that sells clothing and outdoor refreshment gear for trekking, go camping, boulevard biking, mountain biking, rock hiking, ice mountaineering, skiing, avalanche protection, snowboarding, fly fishing, kayaking, rafting, road and trace running, and many more.
HH runs their entire online infrastructure on multiple java based web applications and other web framework applications running on AWS. The HH is capturing clickstream data and use custom-build recommendation engine to recommend products which eventually improve sales, understand customer preferences and already using AWS Kinesis Streams (KDS) to collect events and transaction logs and process the stream. Multiple departments from HH use different streams to address real-time integration and induce analytics into their applications and uses Kinesis as the backbone of real-time data integration across the enterprise.
HH uses a VPC to host all their applications and is looking at integration of kinesis into their web application. To understand the network flow behavior based on every 15 minutes, HH is looking at aggregating data based on the VPC logs for analytics. VPC Flow Logs have a capture window of approximately 10 minutes. What kind of queries can be used to capture aggregates based on each client for every 15 mins using Amazon Kinesis Data Analytics. Select 1 option.

Answer options:

A.Stagger Windows queries
B.Tumbling Windows queries
C.Sliding windows queries
D.Continuous queries

Answer: A
Option A is correct -Stagger windows query, A query that aggregates data using keyed time-based windows that open as data arrives. The keys allow for multiple overlapping windows. This is the recommended way to aggregate data using time-based windows.
VPC Flow Logs have a capture window of approximately 10 minutes. But they can have a capture window of up to 15 minutes if you`re aggregating data on the client. Stagger windows are ideal for aggregating these logs for analysis.
https://docs.aws.amazon.com/kinesisanalytics/latest/dev/stagger-window-concepts.html
Option B is incorrect -Tumbling Windows query, A query that aggregates data using distinct time-based windows that open and close at regular intervals.
https://docs.aws.amazon.com/kinesisanalytics/latest/dev/tumbling-window-concepts.html
Option C is incorrect -Sliding windows query, A query that aggregates data continuously, using a fixed time or rowcount interval.
https://docs.aws.amazon.com/kinesisanalytics/latest/dev/sliding-window-concepts.html
Option D is incorrect -Continuous Query is a query over a stream executes continuously over streaming data. This continuous execution enables scenarios, such as the ability for applications to continuously query a stream and generate alerts.
https://docs.aws.amazon.com/kinesisanalytics/latest/dev/continuous-queries-concepts.html