Articles in this section

Setup Guide: ActivTrak's SQL Access

Unlock the power of ActivConnect and access your ActivTrak data through a native SQL interface. ActivConnect (Powered by BigQuery) leverages the native Google BigQuery user interface to simplify access to your data. You’ll be able to access and analyze millions of rows of data, bringing the power of SQL tools you are already familiar with. 

ActivConnect is available as an add-on for customers on a paid plan. Learn more about ActivConnect here.

Contents

Requirements

  • ActivTrak paid plan and the ActivTrak ActivConnect Add-on. Learn more here.
  • ActivConnect user name and password will be in the format of [account_number]@activtrak.us. Your account number is in the Account Information menu in ActivTrak; access it via the circle icon in the top right corner.

Note: While all tables are available to all ActivConnect subscription plans, the data available within each table will vary based on your specific ActivTrak subscription plan type. See details in the ActivConnect Data Glossary.

Accessing Your Data

  1. Navigate to https://console.cloud.google.com
  2. Enter your [account_number]@activtrak.us email address
  3. Enter your password (you may be prompted to change the password if this is the first time accessing your ActivConnect account)
SQL-1.png

Search for BigQuery in the search bar and select BigQuery to open the Google BigQuery interface:

SQL-2.png

Basic BigQuery Navigation

Below are the main objects you should be familiar with. Please refer to Google BigQuery documentation for a complete list of capabilities. 

  1. Billing Project: If you are accessing ActivConnect with the provided ActivTrak account, the billing project should be "us-activtrak-ac-prod"
    • Click the project picker at the top of BigQuery Studio to select a project
    • Select the "activtrak.us" organization from the dropdown in the top left of the pop-up window
    • Select the "All" filter and search for "us-activtrak-ac-prod"
    • Select "us-activtrak-ac-prod" as your billing project
  2. Dataset: This will be your ActivTrak account number.
  3. Views: These views contain your ActivTrak data. Please refer to the ActivConnect Data Glossary for detailed information about each view.
  4. Query Function: This will open the SQL Query editor
  5. Navigation Tabs: You can organize your work in multiple tabs when working with multiple queries
SQL-3.png

 

The Query editor will open once you select the desired ActivConnect table and click the Query Function. Below are the main components of the query editor.

  1. Query Editor: This is where you will enter your SQL query
  2. Validation: Look for any errors in your query; if everything is correct, you will see the Green Check before running the query
  3. Run: Click Run to execute the query
  4. Query Results: The output of the query will be displayed here
  5. Save Results: Alternatively, if you wish to export the results, you can select the multiple export options from this menu:
SQL-4.png

Sample Queries

List Apps or Sites pending Classification

Important: Replace 'xxxxxx' with your ActivTrak account number

SELECT
  
 COUNT(DISTINCT(user_id))as user_count,
  
  SUM(duration_seconds)AS time_in_app_hr,
  
  application_or_site,
  
  website,
  
  application,
  
  executable,
  
  category,
  
  productivity
  
  FROM
  
  `us-activtrak-ac-prod.xxxxxx.daily_application_summary`
  
  WHERE
  
  productivity ='UNDEFINED' or category is null
  
  GROUPBY
  
  application_or_site,
  
  website,
  
  application,
  
  executable,
  
  category,
  
  productivity
  
  ORDERBY
  
  time_in_app_hr DESC

Working Hours Report

Important: Replace 'xxxxxx' with your ActivTrak account number

SELECT

   local_date,

   day_type,

   user_name,

   utilization_level,

   TIME(first_activity_datetime)AS first_activity,

   TIME(last_activity_datetime) AS last_activity,

   SUM(productive_active_duration_seconds+productive_passive_duration_seconds)/3600 AS productive_hours,

   SUM(unproductive_active_duration_seconds+ unproductive_passive_duration_seconds)/3600 AS unproductive_hours,

   SUM(total_duration_seconds)<><>3600 AS total_hours

  FROM

   `us-activtrak-ac-prod.xxxxxx.daily_user_summary`

  GROUP BY

   1,

   2,

   3,

   4,

   5,

   6

  ORDER BY

   local_date DESC
Was this article helpful?
3 out of 3 found this helpful