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Data Extraction & Storage

Costa Rica

GitHub brown9804

Last updated: 2025-07-17

Wiki

Feature Description
Unified Data Integration Combines citizen and professional data integration
Connectivity Supports over 100 different data sources
Automation Uses AI and metadata for data enrichment
Scalability Handles large-scale data operations efficiently
Security Ensures data security and compliance

Data Extraction & Storage Capabilities

graph LR
    A[Microsoft Fabric Capabilities]
    
    subgraph Extraction
        direction TB
        B1[Relational Databases]
        B2[Non-Relational Databases]
        B3[Data Lakes]
        B4[Data Warehouses]
        B5[APIs]
        B6[File Systems]
        B7[Cloud Services]
        B8[Streaming Data]
    end
    
    subgraph Storage
        direction TB
        C1[Data Lakes]
        C2[Data Warehouses]
        C3[Databases]
        C4[File Systems]
        C5[Data Lakehouses]
    end
    
    A --> Extraction
    A --> Storage
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Capability Type Source/Storage Type Examples
Extraction Relational Databases SQL Server, Oracle, MySQL, PostgreSQL
Extraction Non-Relational Databases MongoDB, Cassandra
Extraction Data Lakes Azure Data Lake, Amazon S3
Extraction Data Warehouses Azure Synapse Analytics, Snowflake
Extraction APIs REST APIs, OData
Extraction File Systems CSV, JSON, XML files
Extraction Cloud Services Azure Blob Storage, Google Cloud Storage
Extraction Streaming Data Kafka, Event Hubs
Storage Data Lakes Azure Data Lake Storage, Amazon S3
Storage Data Warehouses Azure Synapse Analytics, Snowflake
Storage Databases SQL Server, PostgreSQL, MySQL
Storage File Systems Local and cloud-based file storage
Storage Data Lakehouses Combining data lakes and data warehouses

Secure Data Extraction

Some key aspects:

  1. Authentication and Access Control
    • Microsoft Entra ID: All interactions with Fabric are authenticated using Microsoft Entra ID, ensuring secure access from any device and network.
    • Role-Based Access Control (RBAC): Access to data is managed based on user roles, ensuring that only authorized personnel can access sensitive data.
  2. Data Encryption
    • Data in Transit: All data transferred within Fabric is encrypted by default, protecting it from interception during extraction.
    • Data at Rest: Data stored in Fabric is automatically encrypted, ensuring it remains secure even when not in use.
  3. Network Security
    • Private Links and Conditional Access: Fabric can use private links and conditional access policies to regulate and secure data access, especially for data behind firewalls or within private networks.
    • Trusted Access: Fabric can securely connect to data sources protected by firewalls or private networks, ensuring data is not exposed to the public internet.
  4. Compliance and Governance
    • Compliance Standards: Fabric supports a wide range of compliance standards, ensuring data security and regulatory compliance.
    • Governance Tools: Features like data lineage, information protection labels, and data loss prevention help manage and secure data throughout its lifecycle.
  5. Automation and Monitoring
    • Automated Security Protocols: Security protocols, including access controls and encryption, are automated to reduce human error and ensure consistent application.
    • Threat Monitoring: Continuous monitoring for vulnerabilities and threats helps maintain a secure environment.
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Refresh Date: 2025-07-18