Create a real-time data pipeline with Amazon Kinesis to record live streams (such as clickstream or Internet of Things data), process them using AWS Lambda or Kinesis Data Analytics, store the raw data in S3, and then import the processed output into Redshift. Lastly, build QuickSight dashboards to see real-time trends such as fraud detection, sensor monitoring, and user activity.

Create a centralized data lake on Amazon S3 to house both structured and unstructured data from RDS, DynamoDB, and Kinesis, among other sources. For ETL and schema discovery, use AWS Glue; for data querying, use Athena; and for data security, use IAM and KMS. QuickSight provides analysts with direct access to and visualization of data for reporting and insights.

To make a BI solution, get sales and customer data from RDS, change it with Glue, and then load it into Redshift so that it can be queried more easily. Use Step Functions to create automated pipelines and QuickSight dashboards to help businesses keep track of key performance indicators (KPIs) like revenue, retention, and product performance.