Functional Analytics Center of Excellence

Welcome to the FACE of Data Handbook

The FACE (functional analytics center of excellence) is a cross-functional group of functional analytics teams that aim to make our teams more efficient by solving and validating shared data questions which results in cohesive measurement approaches across teams. {: .alert .alert-success}

Context

The central data team serves as the hub for all of our “spoke” functional analytical teams; however, we have an opportunity to establish spokes between the spokes. Enter: the creation of the functional analytics center of excellence (FACE).

FACE Teams: what functional analytics teams are participating?

Objectives of the FACE

• Efficiency: it is not uncommon for our teams to be asked similar questions (eg how are trials converting) but it is inefficient and duplicative for each team to tackle these questions on our own.
• Alignment: in cases where we are tackling similar questions, we need alignment of the assumptions and methodology we are using to answer those questions. The FACE ensures we all deliver cohesive data stories.
• Knowledge Share: this forum will give us a formal venue to learn from one another as opposed waiting for organic moments of knowledge sharing.

Outputs of the FACE

• Cadence: our teams will meet at least once every month if not more. We will knowledge share, align on joint quarterly projects, and develop/prioritize joint asks we have of the central data team. We will also have fun #StaySpoke.
• Consolidated asks to central data team: we have an opportunity to streamline, consolidate, and prioritize our asks to the central data team. We also partner with the central data team on data program-level evaluations and decisions (eg BI tooling).
• Subject Matter Expert Lookup: we will develop a documented list of people and their associated areas of expertise. SME’s will also be able to document their source of truth resources (eg snippets, dashboards, reports).
• Quarterly Projects: we will propose and pick cross-functional projects for us to work on quarterly. This will make us all more efficient by assigning 1 DRI with 2 or more code reviewers.
• Peer Review + Assumptions Approval: as a part of the quarterly projects, we will establish a code peer review and assumptions approval process that will ensure we will all be enthusiastic adopters of the ultimate output.
• Code Repo: after a project has gone through the peer review and assumptions approval process, we will commit it to a repo that any data person can leverage in their work.

Examples: what are the types problems the FACE tackles?

• How do free and trial sign-ups convert?
• How do we link namespaces to Salesforce accounts?
• How do we link leads/INQ to Salesforce accounts?
• How do we identify business emails v. junk account emails?

Working With Us

• Slack channel: #functional_analytics_center_of_excellence
• Open an issue in our Functional Analytics Center of Excellence project
• Join our biweekly meetings or monthly project turn and shares: ask in our Slack channel
• Read our meeting notes and watch meeting recordings [access required]

Resources and Projects

• Source of Truth Fields for Reporting: WIP reference page for analysts, the output of Q1FY23 FACE quarterly project
• Email Domain Classification

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