Data Storage and Classification

This section offers a practical look at how Soundspace handles data storage and classification. Given the different roles and responsibilities within the organization, the processes are tailored to fit the needs of specific audiences like IT Ops and Product Analysts.

Data Storage

Data Gathering Teams

• Temporary Storage: Teams initially store raw data in cloud database or Airtable for immediate analysis. This data is usually in a semi-structured format and requires cleaning and validation.

• Data Handoff: After initial cleaning, the data is handed off to IT Ops through secure channels for storage in the central repository.

IT Ops:

• Central Repository: IT Ops manages a secure central repository, where all cleaned and validated structured data resides. This database integrates with HubSpot and other CRM tools.

• Backup and Security: Backups are performed weekly, and multiple layers of security protocols are implemented to safeguard against unauthorized access.

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Data Classification

Data Gathering Teams

• Field Naming and Classification: Team members consult the Data Dictionary to ensure that all fields are correctly named using the underscore_case format and appropriately classified.

• Unstructured Data: Analysts also deal with unstructured or offline data, like customer feedback from emails or in-person conversations. This data is tagged and categorized manually before being stored in specialized databases designed for unstructured data

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Adding New Fields to the Data Dictionary

The Data Dictionary serves as the central reference for all data fields and their classifications. As Soundspace evolves, there may be a need to add new fields to the Data Dictionary.

IT Ops:

• Data Dictionary Management: IT Ops manages the Data Dictionary, which is a living document continually updated to reflect new data fields and categories.

• Data Audits: Quarterly audits are conducted to ensure all stored data adheres to the classification criteria outlined in the Data Dictionary.

1. Proposing New Fields: Any team member can propose a new field if they identify a gap or a new data requirement. This proposal should be documented, specifying the field name, data type, validation rules, and the reason for its addition.

2. Initial Review by Data Team: The proposal is first reviewed by the Data Team, which includes Product Analysts and IT Ops. They assess the necessity and feasibility of the new field.

3. Stakeholder Approval: If the Data Team approves, the proposal is then sent to key stakeholders for final approval. This includes the heads of Revenue and Operations Stacks, and any other relevant stack leads.

4. Implementation: Once approved, IT Ops is responsible for adding the new field to the central repository, and updating the Data Dictionary.

5. Communication: After the new field has been added, IT Ops will communicate this change to all relevant teams to ensure everyone is aware and can start utilizing the new field appropriately.