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Charter.md

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Project Charter

Business background

  • Who is the client, what business domain the client is in.
  • What business problems are we trying to address?

Scope

  • What data science solutions are we trying to build?
  • What will we do?
  • How is it going to be consumed by the customer?

Personnel

  • Who are on this project:
    • Microsoft:
      • Project lead
      • PM
      • Data scientist(s)
      • Account manager
    • Client:
      • Data administrator
      • Business contact

Metrics

  • What are the qualitative objectives? (e.g. reduce user churn)
  • What is a quantifiable metric (e.g. reduce the fraction of users with 4-week inactivity)
  • Quantify what improvement in the values of the metrics are useful for the customer scenario (e.g. reduce the fraction of users with 4-week inactivity by 20%)
  • What is the baseline (current) value of the metric? (e.g. current fraction of users with 4-week inactivity = 60%)
  • How will we measure the metric? (e.g. A/B test on a specified subset for a specified period; or comparison of performance after implementation to baseline)

Plan

  • Phases (milestones), timeline, short description of what we'll do in each phase.

Architecture

  • Data

    • What data do we expect? Raw data in the customer data sources (e.g. on-prem files, SQL, on-prem Hadoop etc.)

  • Data movement from on-prem to Azure using ADF or other data movement tools (Azcopy, EventHub etc.) to move either

    • all the data,
    • after some pre-aggregation on-prem,
    • Sampled data enough for modeling

  • What tools and data storage/analytics resources will be used in the solution e.g.,

    • ASA for stream aggregation
    • HDI/Hive/R/Python for feature construction, aggregation and sampling
    • AzureML for modeling and web service operationalization

  • How will the score or operationalized web service(s) (RRS and/or BES) be consumed in the business workflow of the customer? If applicable, write down pseudo code for the APIs of the web service calls.

    • How will the customer use the model results to make decisions
    • Data movement pipeline in production
    • Make a 1 slide diagram showing the end to end data flow and decision architecture
      • If there is a substantial change in the customer's business workflow, make a before/after diagram showing the data flow.

Communication

  • How will we keep in touch? Weekly meetings?
  • Who are the contact persons on both sides?