Use Cases for Analyzing Streaming Data
Question
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 java based web 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 Producer Library to collect events and transaction logs and process the stream. HH is looking at processing and analyzing streaming data using standard SQL which enables to quickly author and run powerful SQL code against streaming sources using AWS Kinesis Analytics.
What kind of use cases can be realized using this capability?Select 3 options.
Answers
Explanations
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A. B. C. D. E.Answer: A,B,D.
Amazon Kinesis Data Analytics allows processing and analyzing streaming data using standard SQL which enables to quickly author and running powerful SQL code against streaming sources to perform time series analytics, feed real-time dashboards, and create real-time metrics.
https://docs.aws.amazon.com/kinesisanalytics/latest/dev/what-is.htmlHH is using AWS Kinesis Producer Library to collect events and transaction logs and process the stream. They are looking at processing and analyzing streaming data using standard SQL, which enables them to quickly author and run powerful SQL code against streaming sources using AWS Kinesis Analytics. Here are three use cases that can be realized using this capability:
A. Metrics over time windows, thereby streaming data to Amazon S3 or Amazon Redshift through Kinesis stream: Kinesis Analytics can help HH to create real-time metrics over time windows to gain insights into their customers' behavior. With Kinesis Analytics, HH can write SQL queries to calculate various metrics such as average session duration, bounce rate, and time spent on each page. These metrics can be streamed to Amazon S3 or Amazon Redshift through Kinesis stream for further analysis.
B. Aggregate and Process streaming data results to feed real-time dashboards: HH can use Kinesis Analytics to aggregate and process streaming data in real-time and feed the results to real-time dashboards. Kinesis Analytics can help to create SQL queries to aggregate and filter the data from Kinesis stream, and feed the results to a real-time dashboard for monitoring and analysis. Real-time dashboards can provide HH with insights into their website's performance, customer behavior, and sales trends.
C. Data warehousing ETL Engine to pre-process before loading into target applications: HH can use Kinesis Analytics as a data warehousing ETL engine to pre-process data before loading it into target applications. Kinesis Analytics can help to transform and enrich data from Kinesis stream, and load it into target applications such as Amazon S3, Amazon Redshift, or Amazon RDS databases. This can help HH to analyze their data and gain insights into their customers' behavior, sales trends, and website performance.
D. Enable Custom Metrics and supports real-time monitoring, notifications, and alarms: Kinesis Analytics can enable HH to create custom metrics to monitor their website's performance, customer behavior, and sales trends. Kinesis Analytics can help to create SQL queries to calculate custom metrics and support real-time monitoring, notifications, and alarms. This can help HH to detect and respond to issues in real-time and improve their website's performance.
E. Batch Integration and ingesting data into DWH and RDS databases: Kinesis Analytics can also help HH to integrate batch data with their streaming data and ingest it into data warehousing and relational database systems such as Amazon S3, Amazon Redshift, and Amazon RDS. Kinesis Analytics can help to create SQL queries to transform, aggregate, and filter batch data, and integrate it with streaming data for further analysis. This can help HH to gain insights into their customer behavior, sales trends, and website performance.
