Operational Data Layer (ODL) Benefit:

💎 Single Source of Truth: Provides a unified data repository for the organization.

🔍 Real-Time Analytics: Enables real-time data analysis and decision-making.

🔄 Gradual Refactoring: Allows incremental data model changes without disrupting existing systems.

🛡️ Minimizes Disruption: Isolates changes, reducing impact on production systems.

🔒 Isolated from Raw Customer Data: Separates sensitive data from operational data.

🌐 Fulfill GDPR: Ensures compliance with the General Data Protection Regulation.

🔐 Fulfill PII: Manages personally identifiable information securely.

What an Operational Data Layer (ODL) Can Do? 🤔

💾 Change Data Capture (CDC): Capture changes to the data in real-time or near-real-time, allowing for efficient updates and synchronization between different systems.

🚮 Remove Useless Data: Help identify and remove irrelevant or redundant data, optimizing storage and processing resources.

📊 Read-Heavy Operations for Analytics, Historical Data: Serve as a dedicated layer for analytical and historical data, allowing for efficient and high-performance read operations to support advanced analytics and reporting.

🔖 Add Metadata to Record: Enrich the data with additional metadata, such as timestamps, source information, or data quality metrics, to provide more context and enhance the overall data quality.

🔍 Merge Data to Single Customer View for Advanced Analytics: Consolidate and integrate data from multiple sources to create a unified, 360-degree view of the customer, enabling more advanced analytics and personalized experiences.

💳 Determine Spending on Each Category: Analyze and categorize customer spending patterns, allowing businesses to better understand their customers' behaviors and preferences.

🕰️ Real-Time View: Reduced application complexity - read & write operations together.

💫 Delta Load Mechanism: Identify and load only the changes or "deltas" in the data, instead of re-loading the entire dataset, making the data integration process more efficient.

MongoDB App Services: 🌐

🔄 Atlas Device Sync: Synchronize data between client apps and MongoDB Atlas, enabling offline-first mobile and web applications.

⚡ Serverless Cloud Functions: Run custom server-side logic in the cloud without managing any infrastructure.

🔒 Declarative Access Rules: Define fine-grained access controls for your data, ensuring secure data access.

🔍 Flexible Data API: Efficiently query, filter, and manipulate your MongoDB Atlas data through a RESTful interface.

🔗 GraphQL API: Fetch and manipulate data efficiently using a powerful query language and runtime.

MongoDB App Services Advantage: 💪

• Write & host an application in a fully managed cloud environment
• Bring products to market faster
• Control data access using rules: existing authentication systems
• Enrich data for application requirement

Operational Data Layer Real-World Use Case: 🌍

Situation: Cloud-based HR and financial solutions

Before: 💸 Landing pages required 15 or more expensive queries to present a single view to the customer of their personal accounts, savings, mortgages.

After: 💰 Serve single query by ODL, cut cost, fulfill PSD2 payments services.

Advantage: ⏱️ Save administration operation time.

Editor

Danny Chan, specialty of FSI and Serverless

Kenny Chan, specialty of FSI and Machine Learning