Commit 23d4096f authored by Naheil McAvinue's avatar Naheil McAvinue Committed by Cynthia "Arty" Ng
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Reorganize Enterprise Data top-level folders in handbook

parent 77cbc1a8
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@@ -41,7 +41,7 @@ A Key Review should not be cancelled without permission. Permission to cancel or
Required invitees are members of E-Group, the CoS to the CEO, the EBA to the CFO, and the EBAs to the CEO.
Optional attendees are other team members as designated by their E-Group leader.

Key Review Meetings may contain [material non-public information (MNPI)](/handbook/enterprise-data/data-management/#data-categorization). As materials are limited access, participation is limited. Key Review agendas and recordings should not be shared with anyone not on the invite.
Key Review Meetings may contain [material non-public information (MNPI)](/handbook/enterprise-data/data-governance/data-management/#data-categorization). As materials are limited access, participation is limited. Key Review agendas and recordings should not be shared with anyone not on the invite.

If the Key Review meeting will not contain MNPI, it can be privately livestreamed to GitLab Unfiltered.

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@@ -36,7 +36,7 @@ canonical_path: "/company/okrs/2018-q4/"
- CFO: Use data to drive business decisions
  - Director of Business Operations: Create scope for User Journey that is documented and mapped to key data sources. *50%*
  - Director of Business Operations: Top of funnel process and metrics defined and aligned with bottom of funnel. *70%*
    - Data & Analytics: Able to define and calculate Customer Count, MRR and ARR by Customer, Churn by Cohort, Reason for Churn *75%- - Some metrics still require [review](/handbook/enterprise-data/data-quality/)
    - Data & Analytics: Able to define and calculate Customer Count, MRR and ARR by Customer, Churn by Cohort, Reason for Churn *75%- - Some metrics still require [review](/handbook/enterprise-data/data-governance/data-quality/)
  - Director of Business Operations: Looker Explores generated for Customer Support, PeopleOps, GitLab.com Event Data, Marketing Data *100%*
    - Data & Analytics: Single Data Lake for all raw and transformed company data - migration to Snowflake complete with DevOps workflow in place, GitLab.com production data extracted and modelled *75%*
    - Data & Analytics: Configuration and Business processes documented with integrity tests that sync back with upstream source (SFDC), dbt docs deployed *100%*
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@@ -334,7 +334,7 @@ This [fiscal quarter](/handbook/finance/#fiscal-year) will run from November 1,
    1. PAO: No material weaknesses identified by Audit Firm. => 90% (internal controls work not finalized by auditor)
1. **CFO: Build a scalable data infrastructure that ensures completeness of data, quality and ability for anyone in the organization to access data and perform analysis.**
    1. Data Team: [Embedded/Central analyst/engineer model implemented so each function has at least one embedded data analyst.](https://gitlab.com/gitlab-data/analytics/issues/3023)
    1. Data Team: Sensitive data [is identified](https://gitlab.com/groups/gitlab-data/-/epics/74) in 66% of [data sources](/handbook/enterprise-data/platform/#extract-and-load) at the database object level (columns, tables, etc.) [in a file in our repository for use in automated and dynamic modeling, administering, and auditing of the warehouse.](https://gitlab.com/groups/gitlab-data/-/epics/65)
    1. Data Team: Sensitive data [is identified](https://gitlab.com/groups/gitlab-data/-/epics/74) in 66% of [data sources](/handbook/enterprise-data/platform/) at the database object level (columns, tables, etc.) [in a file in our repository for use in automated and dynamic modeling, administering, and auditing of the warehouse.](https://gitlab.com/groups/gitlab-data/-/epics/65)
    1. Data Team: [66% of data sources of Data quality measures and tests documented and implemented for data sources.](https://gitlab.com/groups/gitlab-data/-/epics/63)
1. **CFO: Create an IT organization that prepares the company for growth over next 18 months.**
    1. IT: Create an IT SLA framework and issue initial target of less than three days.
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@@ -71,7 +71,7 @@ The table below represents the steps a CSM would typically take in Gainsight. Pl
- [Product Usage Data FAQs](/handbook/customer-success/product-usage-data/using-product-usage-data-in-gainsight/)
- [Use Case Adoption (definitions)](/handbook/customer-success/product-usage-data/use-case-adoption/)
- [Customer Health Scoring](/handbook/customer-success/customer-health-scoring/)
- [Product Usage Data - Data Team](/handbook/enterprise-data/data-catalog/product-usage-data/)
- [Product Usage Data - Data Team](https://internal.gitlab.com/handbook/enterprise-data/data-catalog/product-usage-data/)
- [License Utilization](/handbook/customer-success/product-usage-data/use-case-adoption/)
- [Maturity Scoring](/handbook/customer-success/product-usage-data/maturity-scoring/)
- [Product usage playbooks with usage metrics](/handbook/customer-success/product-usage-data/metrics-based-playbooks/)
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@@ -122,4 +122,4 @@ The collection and use of operational data will governed in accordance with the
- [Product Usage in Gainsight FAQ Guide](/handbook/customer-success/product-usage-data/using-product-usage-data-in-gainsight/)
- [Metrics Dictionary](https://docs.gitlab.com/ee/development/internal_analytics/metrics/metrics_dictionary.html)
- [Analytics Instrumentation Overview](/handbook/product/product-processes/analytics-instrumentation-guide/) (details on operational data)
- [Email Marketing Data Mart](/handbook/enterprise-data/data-catalog/email-data-mart/)
- [Email Marketing Data Mart](https://internal.gitlab.com/handbook/enterprise-data/data-catalog/email-data-mart/)
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