Skip to content
This repository has been archived by the owner on Oct 12, 2023. It is now read-only.

Latest commit

 

History

History
64 lines (38 loc) · 2.73 KB

Exit Report.md

File metadata and controls

64 lines (38 loc) · 2.73 KB

Exit Report of Project for Customer

Instructions: Template for exit criteria for data science projects. This is concise document that includes an overview of the entire project, including details of each stage and learning. If a section isn't applicable (e.g. project didn't include a ML model), simply mark that section as "Not applicable". Suggested length between 5-20 pages. Code should mostly be within code repository (not in this document).

Customer: <Enter Customer Name>

Team Members: <Enter team member' names. Please also enter relevant parties names, such as team lead, Account team, Business stakeholders, etc.>

Overview

<Executive summary of entire solution, brief non-technical overview>

Business Domain

<Industry, business domain of customer>

Business Problem

<Business problem and exact use case(s), why it matters>

Data Processing

<Schema of original datasets, how data was processed, final input data schema for model>

Modeling, Validation

<Modeling techniques used, validation results, details of how validation conducted>

Solution Architecture

<Architecture of the solution, describe clearly whether this was actually implemented or a proposed architecture. Include diagram and relevant details for reproducing similar architecture. Include details of why this architecture was chosen versus other architectures that were considered, if relevant>

Benefits

Company Benefit (internal only. Double check if you want to share this with your customer)

<What did our company gain from this engagement? ROI, revenue, etc>

Customer Benefit

What is the benefit (ROI, savings, productivity gains etc) for the customer? If just POC, what is estimated ROI? If exact metrics are not available, why does it have impact for the customer?>

Learnings

Project Execution

<Learnings around the customer engagement process>

Data science / Engineering

<Learnings related to data science/engineering, tips/tricks, etc>

Domain

<Learnings around the business domain, >

Product

<Learnings around the products and services utilized in the solution >

What's unique about this project, specific challenges

<Specific issues or setup, unique things, specific challenges that had to be addressed during the engagement and how that was accomplished>

Links

<Links to published case studies, etc.; Link to git repository where all code sits>

Next Steps

<Next steps. These should include milestones for follow-ups and who 'owns' this action. E.g. Post- Proof of Concept check-in on status on 12/1/2016 by X, monthly check-in meeting by Y, etc.>

Appendix

<Other material that seems relevant – try to keep non-appendix to <20 pages but more details can be included in appendix if needed>