The hottest Data Models Substack posts right now

And their main takeaways
Category
Top Technology Topics

What I Learned This Week #3

Eventually Consistent • 59 implied HN points • 09 Jun 24
🕹 Technology Data Models Edge Computing
  1. Data models are crucial and should be chosen based on relationships among data elements and required access patterns. Graph modeling can be beneficial for many-to-many relationships, while documents work better for one-to-many relationships. Modeling affects performance.
  2. Memory access patterns significantly impact computation time by influencing caching behavior. The chosen pattern determines cache hits/misses and the level from which data is retrieved.
  3. In edge computing, while databases like Postgres rely on raw TCP sockets, WebSockets are preferred for security reasons. WebSockets provide similar benefits while maintaining secure and standardized communication channels.

You can take your gold and shove it...

davidj.substack • 59 implied HN points • 13 Jan 25
🕹 Technology Data architecture Data processing Analytics Data Models Software Development
  1. The gold layer in data architecture has drawbacks, including the loss of information and inflexibility for users. This means important data could be missing, and making changes is hard.
  2. Universal semantic layers offer a better solution by allowing users to request data in plain language without complicated queries. This makes data use easier and more accessible for everyone.
  3. Switching from a gold layer to a semantic layer can improve efficiency and user experience, as it avoids the rigid structure of the gold layer and adapts to user needs more effectively.

sqlmesh cube_generate build part 2

davidj.substack • 23 implied HN points • 18 Dec 24
🕹 Technology Data Models Command-line Software Development
  1. The main goal is to create a command that generates metadata to build a semantic layer for SQL models. This is important because it helps in understanding the structure and relationships within the data.
  2. AI can enhance the process by taking the generated metadata and improving it for better usability. Using tools like OpenAI can make the process easier and faster.
  3. There's an ongoing focus on creating practical solutions rather than aiming for perfection. It's okay to make adjustments and improvements along the way as you learn what works best.

Data Models, Types, or Schemas?

The API Changelog • 4 implied HN points • 14 Feb 25
🕹 Technology APIs Data Models Software Development Programming Data Management
  1. Naming things is tough, especially when it comes to defining API data. Different people use different terms like data model, data type, or schema, which can lead to confusion.
  2. A data model helps to represent and organize information, while a data type defines the kind of data values it can hold. However, people often associate data types with simple categories like strings and numbers.
  3. The term 'schema' is commonly used to describe the structure and format of API data. Many standards, like OpenAPI and GraphQL, reference schemas to clarify how to define input and output data.
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Will data served as language models overtake the role of semantic/linked data?

Living Systems • 2 HN points • 09 Aug 23
🕹 Technology Data Models Language Models Information Retrieval Artificial Intelligence
  1. The role of language models in serving data is being considered over semantic/linked data.
  2. Language models make data self-sufficient and self-describing, reducing the need for complex data schemas.
  3. Large language models present an opportunity for flexible data access and communication between models, potentially via linked data.