Data Product Requirement Document Template

• 5 min read

A. Requirement Assessment

Analytics Portfolio Assessment Partners must demonstrate how they assess current state and customer requirements to ensure adequate pre migration or pre-deployment planning and sizing are performed. Assessment must include areas specific to deploying analytics solutions:

Business need

  • Current pain points, challenges, and end user needs
  • Product fit and gaps to identify which product will best serve the customer’s needs
  • Data storage needs from a business standpoint – volume, type, location, current state vs future state
  • Data governance and compliance
  • Budget

Application Landscape

  • Current infrastructure or greenfield physical infrastructure
  • Logical architecture and requirements for migration, if applicable
  • Information for all applications, services, and software-as-a-service BI platforms (for example, PowerBI.com or Tableau online).

Performance Benchmarks

Assess and document application performance requirements and data transfer requirements.

User Personas

  • Document user roles, how each will use the data, how each will access the data
  • Stakeholder engagement across business user roles, BI, analytics and/or data science roles

Data needs

At the workload level, assess which data needs must be fulfilled t0 meet stated business requirements around data such as:

  • Type of data, volume, speed that will influence the technology required
  • Data centralization
  • Classification and risk of data involved
  • Identify data sources (on-premises, AWS, Google,etc.) and destination (data storage on Cloud).
  • Identify who or what should consume the data

Networking

Existing infrastructure/networking components that will connect to Cloud to move data and current applications.

Security and Compliance needs

Identity and access management, role-based access control, encryption, industry, and geography- centric compliance requirements, if applicable

Availability,resiliency,and disaster recovery needs

  • Customer expectations once moved toCloud
  • Expected demand and scalability
  • Uptime and SLA

B. Solution Design

Partners must provide solution designs showing a consistent approach that addresses customer requirements captured from the assessment phase. Solution design must show areas specific to deploying analytics solutions:

User Roles

User roles required to deploy the analytics solution (ETL users, analysts, developer, report designer, data scientists, etc.) and establish role-based access

Data Source

Identify all data sources and file types to be ingested.

Data Migration Approach

Outline of the migration approach to be used for the data, if applicable.

Ingestion Engine

Identify the use of a data ingestion engine to extract, transform, load, and clean data. Ingestion engines include but are not limited to native products such as Cloud Data Factory, Fabric Data Factory, Informatica, Data Stage, and Cloud Databricks.

Data Storage

Identify storage type for the ingested data. Data storage can include but is not limited to native products such as Cloud Blob, Cloud Data Lake, Cloud Data Warehouse, Cloud Synapse or OneLake.

Encryption Method

Identify data encryption approach. Data encryption methodology can include but is not limited to Transparent Data Encryption (TDE), masking and Cloud Key Vault.

Analytics Service

Data analysis using Cloud Synapse Analytics OR Cloud Databricks, OR Microsoft Fabric or Dedicated SQL Pool (formerly SQL Data warehouse)

Data Reporting and Visualization

Identify use of the analytics data using data reporting tools including (but not limited to) Power BI, Tableau, MicroStrategy, etc.

DevOps: Considerations for applying DevOps principles

Specify source depot(Visual Studio, Git Repository, etc.)

Coding language

  • Redesign code or plan for backward compatibility
  • Code deployment process.

Landing Zone

Landing zone design must demonstrate how the design considers analytics- specific constraints:

  • RegionalPlanning:Document regional availability of data centers and services.
  • Network and Infrastructure Providers: Document regional availability of networks, providers, and hardware required to deploy.
  • Networking, Network Security Groups, Identity and Access Methods: Identify the use of secure networking for data migration and storage including firewall, networking security groups, VNet and subnet.
  • Implementation evidence ofIdentity and AccessManagement (IAM) and Role Based Access Control (RBAC), data sovereignty & encryption, application security, auditing.
  • Establish a Hub-Spoke architecture or retrofit the existing deployment to separate out the network components of a Hub for optimal performance and security.
  • Use ofSecurity products such asCloud Security Services, M365Security, or other security solutions to secure access to the data.
  • Use of governance tooling to support cost optimization across the environment. After estimating the initial cost, set budgets and alerts at different scopes to proactively monitor the cost.
  • Use of backup and recovery solutions to ensure data retention.
  • Environment must meet requirements for regulatory compliance in the new environment, where applicable, such as GDPR and HIPAA, and implementation through multiple data center regions, as needed.
  • Use of a monitoring solution to provide proactive remediation for the Cloud environment, which is integrated into the customer’s existing monitoring tooling, if appropriate.
  • Use of visualization and alerting considerations for solutions, where appropriate.
  • Demonstrate how this deployment will use the operations baseline to help the customer maintain data ingress, data governance, high availability of data, and solution optimization.

Risk

Addresses the migration risk assessment and mitigation, if applicable.