PART 1

Customer/User Job-to-be-Done or Problem

When consuming Gazelle company dataset I need to be able to have access to it in one location allowing me to run specialized and performant queries in order to build a large scale analysis of company insights for multiple use cases. 

Value to Customers & Users

Data updates, which are to be made regularly in order to provide the most fresh company information with increased quality (including deduplication, removing invalid information, better company trees matching etc.) as a consistent output of NeoETL data processing pipelines, when delivered to Snowflake, provide ability to leverage large company intelligence database in a flexible environment.

Value to Lightcast

Opens up early feedback loops for customer input on our product roadmap and exposes the data internally rapidly.

Target User Role/Client/Client Category

Gazelle clients that value access to the complete large company dataset

Delivery Mechanism

Snowflake

Success Criteria & Metrics

Gazelle Beta Golden Records for companies accessible for clients through Snowflake.
Data Dictionary available to the clients is fully describing the data available.
Subsequent updates to Gazelle Beta Golden Records for companies are automatically made available in Snowflake with some release system.

Aspects that are out of scope (of this phase)

No Contact information to avoid PII for now

PART 2

Solution Description

Early UX (wireframes or mockups)

<FigmaLink>

Non-Functional Attributes & Usage Projections

Consider performance characteristics, privacy/security implications, localization requirements, mobile requirements, accessibility requirements

Dependencies

Is there any work that must precede this? Feature work? Ops work? 

Legal and Ethical Considerations

Just answer yes or no.

High-Level Rollout Strategies

• Initial rollout to [internal employees|sales demos|1-2 specific beta customers|all customers]

  • If specific beta customers, will it be for a specific survey launch date or report availability date 

• How will this guide the rollout of individual stories in the epic?

• The rollout strategy should be discussed with CS, Marketing, and Sales.

• How long we would tolerate having a “partial rollout” -- rolled out to some customers but not all

Risks

Focus on risks unique to this feature, not overall delivery/execution risks. 

Open Questions

1. Grooming session need to understand steps

2. Clear definition of MVP

   1. Certain data fields we can’t surface

   2. Finish Golden Records

Complete with Engineering Teams

Estimated Costs

Direct Financial Costs

Are there direct costs that this feature entails? Dataset acquisition, server purchasing, software licenses, etc.?

Team Effort

Each team involved should give a general t-shirt size estimate of their work involved. As the epic proceeds, they can add a link to the Jira epic/issue associated with their portion of this work.