You can achieve the above result, if your dimension data is like this.
Dimensions: RoomName=room1, Sex=Male, Unit: Count, Timestamp:
2016-10-31T12:30:00Z, Value: 105
Dimensions: RoomName=room1, Sex=Female, Unit: Count, Timestamp:
2016-10-31T12:31:00Z, Value: 115
Dimensions: RoomName=room2, Sex=Male, Unit: Count, Timestamp:
2016-10-31T12:32:00Z, Value: 95
Dimensions: RoomName=room2, Sex=Female, Unit: Count, Timestamp:
2016-10-31T12:33:00Z, Value: 97
If the data point is sent as 90 without sex attribute (Male or Female), you can't get the fine grained information (count by sex) in the result.
Cloudwatch dimension
AWS CloudWatch Logs is a service which is integrated with other services like EC2, CloudTrail etc. You can get data from these services and monitor them for any errors, events etc.
Amazon CloudWatch Logs can be used to monitor, store, and access your
log files from Amazon Elastic Compute Cloud (Amazon EC2) instances,
AWS CloudTrail, Route 53, and other sources. You can then retrieve the
associated log data from CloudWatch Logs.
CloudWatch logs