[Data Product] Dashboard summariser - Cumulative

[Data Product] Dashboard summariser - Cumulative

Summary:

  • Type - Dashboard cumulative summariser

  • Granularity - DAY

  • Computation Level - Level 3

  • Frequency - Runs Daily

Purpose:

The Dashboard summariser is used to compute the

  1. Unique Devices - The total number of unique devices that have ever accessed Diksha (across portal and app)

  2. Learning Experiences - The total number of content play sessions across portal and app to current date.

  3. Hours of interaction - The total time spent on Diksha (i.e. total session time, inclusive of but not limited to content play sessions)

 

Inputs:

         Derived Event : ME_WORKFLOW_SUMMARY

 

Output

{ "eid": "ME_PORTAL_CUMULATIVE_METRICS", "ets": 1544670495619, "syncts": 1544670495619, "metrics_summary": { "noOfUniqueDevices": 1323, "totalContentPlayTime": 29.24, "totalTimeSpent": 35577.22, "totalContentPublished": 4105 } }

Algorithm

Field

Description

Computation

Field

Description

Computation

1

noOfUniqueDevices

This metric tracks the total number of unique devices that have accessed Diksha(Portal and App)

filter by with below fields and compute the total distinct count 

filter((d_period = 0 ) and (d_tag=="all") and (d_content_id=='all')and (d_user_id=='all') and (d_deviceId!='all') and distinctCount(d_device_id)
2

totalDigitalContentPublished 

Number of contents been published

composite search API:

/composite/v3/search

3

totalContentPlaySessions

This metric tracks the total number of content play sessions (Portal and App).

filter with below fields and  aggregating the edata.eks.time_spent field

filter((d_period = 0) and (d_tag=="all") and (d_content_id=='all')and (d_user_id=='all') and (d_mode=='play') and (d_type=='content') and aggregate(m_total_sessions)
4

totalTimeSpent

This metric track the total time spent on Diksha(Portal and App)

filter by with below fields and  aggregating the edata.eks.time_spent field

filter((d_period = 0) and (d_tag=="all") and (d_content_id=='all')and (d_user_id=='all') and (d_type=='app' ||'session') and (d_deviceId=='all') aggregate(m_total_ts)



Conclusion: