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Add a page about the process and spectrum of analytical tools for diving into data and metrics.

Reference: https://www.linkedin.com/feed/update/urn:li:activity:7185592703903019008?commentUrn=urn%3Ali%3Acomment%3A%28activity%3A7185592703903019008%2C7185631020577161216%29&dashCommentUrn=urn%3Ali%3Afsd_comment%3A%287185631020577161216%2Curn%3Ali%3Aactivity%3A7185592703903019008%29

👋 Hi there,

Came across the DPH framework recently and am curious about the Developer build time (DBT) metric that LinkedIn uses.

The document defines DBT as — 

TL;DR: How much time do developers spend waiting for their build tool to finish
its work.
The intention of this metric is to measure the amount of time that human beings
spend waiting for their build tool to complete. This is measured as the
wall-clock time from when the build tool starts a "build" to when it completes.
This measures all human-triggered builds. At present, this includes all
human-triggered builds with the following tools:

• Gradle
• Bazel
• Ember 
• Xcode 

Do you measure tool times as an aggregate?

Or aggregate it basis lifecyles like —

1. Version control (git performance)
2. Application Build
3. Running unit tests
4. Running integration tests
   etc?