Entities and Attributes of Real-Time Analytics
Entities serve as the building blocks of our database, representing the fundamental objects or concepts that need to be stored and managed. Attributes define the characteristics or properties of each entity. Let’s explore each entity and attribute in detail:
1. Event
- event_id (Primary Key): Unique identifier for each event.
- event_type: Type of event (e.g., click, purchase, sign-up).
- timestamp: Timestamp of when the event occurred.
- data: Additional data related to the event.
2. User
- user_id (Primary Key): Unique identifier for each user.
- username: Username of the user.
- email: Email address of the user.
3. Pageview
- pageview_id (Primary Key): Unique identifier for each page view.
- event_id (Foreign Key referencing Event): Identifier of the event associated with the page view.
- user_id (Foreign Key referencing User): Identifier of the user who viewed the page.
- page_url: URL of the page viewed.
4. Purchase
- purchase_id (Primary Key): Unique identifier for each purchase.
- event_id (Foreign Key referencing Event): Identifier of the event associated with the purchase.
- user_id (Foreign Key referencing User): Identifier of the user who made the purchase.
- product_id: Identifier of the product purchased.
- quantity: Quantity of the product purchased.
- amount: Amount of the purchase.
How to Design a Database for Real-Time Analytics
Real-time analytics is becoming increasingly important for businesses to make informed decisions quickly. Designing a relational database for real-time analytics requires careful consideration of the data model, indexing, and query optimization to ensure fast and efficient data processing.
This article will explore the key components involved in designing a database for real-time analytics and we’ll take a look at the details of creating a real-time relational database. We’ll focus on the key components of a successful relational database, such as accurate data modeling, effective strategic indexing, and query optimization.