EPIC list of Data warehouse

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 Creating an Epic list for building a data warehouse using Snowflake involves outlining the high-level objectives and goals of the project. The following is an example of an Epic list for a Snowflake data warehouse project:


**Epic 1: Data Warehouse Architecture**

- Epic Description: Design and establish the overall architecture of the Snowflake data warehouse.

  - Epic Tasks:

    1. Define the architectural requirements and constraints.

    2. Select appropriate Snowflake edition and services.

    3. Set up data warehousing environment within Snowflake.

    4. Define data storage strategy (data lakes, data marts, etc.).

    5. Establish data integration and ETL processes.


**Epic 2: Data Ingestion and Integration**

- Epic Description: Ingest and integrate data from various source systems into the Snowflake data warehouse.

  - Epic Tasks:

    1. Identify source systems and data formats.

    2. Develop data ingestion pipelines.

    3. Establish real-time or batch data integration as needed.

    4. Ensure data quality and transformation processes.

    5. Implement change data capture (CDC) mechanisms.


**Epic 3: Data Modeling and Schema Design**

- Epic Description: Define the data models and schema design for the data warehouse.

  - Epic Tasks:

    1. Create a logical data model.

    2. Develop dimensional and/or normalized data models.

    3. Design star schemas or snowflake schemas.

    4. Define primary and foreign keys.

    5. Implement slowly changing dimensions (SCDs) as required.


**Epic 4: Data Security and Access Control**

- Epic Description: Ensure data security and access control within the Snowflake environment.

  - Epic Tasks:

    1. Define user roles and permissions.

    2. Implement data encryption at rest and in transit.

    3. Establish auditing and monitoring for data access.

    4. Set up multi-factor authentication (MFA) as needed.

    5. Implement data masking and row-level security.


**Epic 5: Data Transformation and ETL**

- Epic Description: Develop ETL processes for data transformation and loading into Snowflake.

  - Epic Tasks:

    1. Create ETL workflows for data cleansing and transformation.

    2. Schedule and automate ETL jobs.

    3. Handle error handling and exception management.

    4. Monitor and optimize ETL performance.

    5. Implement data lineage and tracking.


**Epic 6: Reporting and Analytics**

- Epic Description: Enable reporting and analytics capabilities on top of the Snowflake data warehouse.

  - Epic Tasks:

    1. Select and implement reporting tools (e.g., Tableau, Power BI).

    2. Develop dashboards and reports.

    3. Define self-service analytics capabilities.

    4. Enable ad-hoc querying and exploration.

    5. Ensure performance optimization for queries.


**Epic 7: Data Governance and Compliance**

- Epic Description: Implement data governance and compliance measures within the Snowflake data warehouse.

  - Epic Tasks:

    1. Define data governance policies and standards.

    2. Establish data lineage and metadata management.

    3. Implement data catalog and data dictionary.

    4. Ensure compliance with industry regulations (e.g., GDPR, HIPAA).

    5. Conduct regular data quality assessments.


**Epic 8: Scalability and Performance**

- Epic Description: Ensure the scalability and performance of the Snowflake data warehouse as data volumes grow.

  - Epic Tasks:

    1. Monitor and optimize resource utilization.

    2. Implement auto-scaling and elastic compute.

    3. Conduct performance tuning and query optimization.

    4. Plan for data warehouse capacity expansion.

    5. Implement disaster recovery and high availability measures.


**Epic 9: Training and Documentation**

- Epic Description: Provide training and documentation to ensure that users can effectively utilize the Snowflake data warehouse.

  - Epic Tasks:

    1. Develop user training materials and documentation.

    2. Conduct training sessions for end-users and administrators.

    3. Create knowledge base and FAQs.

    4. Provide ongoing support and resources for users.

    5. Document data warehouse architecture and processes.


**Epic 10: Project Management and Governance**

- Epic Description: Oversee project management and governance for the entire data warehouse implementation.

  - Epic Tasks:

    1. Define project milestones and timelines.

    2. Establish governance and change management processes.

    3. Conduct regular project status meetings.

    4. Monitor project budget and resource allocation.

    5. Ensure alignment with organizational goals.


These epics provide a high-level framework for planning and executing a Snowflake data warehouse project. Each epic can be further broken down into smaller user stories and tasks to facilitate project management and tracking progress.



User story for Snowflakes + Fivetran + ERP

Integrating an ERP SQL database with a Snowflake database using the Fivetran ETL (Extract, Transform, Load) tool involves specific user stories that highlight the functionalities and tasks required for this process. Here are some user stories for this integration:

**User Story 1: Connect ERP Database to Fivetran**
- As a data engineer, I want to set up a connection between our ERP SQL database and Fivetran to enable data extraction and transfer.

**User Story 2: Define Data Sources and Tables**
- As a data analyst, I want to define the specific data sources, tables, and fields from the ERP SQL database that need to be integrated into Snowflake.

**User Story 3: Schedule Data Extraction**
- As a system administrator, I want to schedule regular data extraction from the ERP database using Fivetran, ensuring data is up-to-date in Snowflake.

**User Story 4: Data Transformation and Mapping**
- As a data engineer, I want to configure data transformation and mapping rules within Fivetran to align the ERP data with the schema and format required in Snowflake.

**User Story 5: Incremental Data Loading**
- As a database administrator, I want to implement incremental data loading, ensuring that only new or modified data is transferred from the ERP database to Snowflake.

**User Story 6: Error Handling and Logging**
- As a data engineer, I want to set up error handling and logging mechanisms in Fivetran to capture and report any data transfer issues.

**User Story 7: Data Quality and Consistency Checks**
- As a data analyst, I want to implement data quality and consistency checks within Fivetran to identify and address data discrepancies or anomalies.

**User Story 8: Scheduling and Automation**
- As a system administrator, I want to automate the data extraction, transformation, and loading processes using Fivetran to reduce manual intervention and improve data consistency.

**User Story 9: Data Security and Access Control**
- As a security administrator, I want to ensure that Fivetran's connection and data transfer processes are secure and compliant with access control policies to protect sensitive data.

**User Story 10: Performance Optimization**
- As a database administrator, I want to monitor and optimize the performance of data transfer processes using Fivetran to ensure efficient and timely data integration with Snowflake.

**User Story 11: Data Governance and Compliance**
- As a data governance officer, I want to implement data governance policies within Fivetran to maintain data quality, metadata management, and ensure compliance with industry regulations and organizational standards.

**User Story 12: Documentation and Knowledge Transfer**
- As a project manager, I want to document the entire integration process in Fivetran and provide training to end-users and administrators on how to access and utilize the data in Snowflake.

**User Story 13: Reporting and Analytics Integration**
- As a business analyst, I want to integrate reporting and analytics tools (e.g., Tableau, Power BI) with Snowflake, using data integrated via Fivetran, to enable business users to create reports and dashboards based on ERP data stored in Snowflake.

These user stories help capture the requirements and tasks involved in integrating an ERP SQL database with a Snowflake database using the Fivetran ETL tool. They guide the implementation process and ensure that the integration meets the needs of various stakeholders. The user stories can be further refined and prioritized as needed.

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