Data Offering Workflow With Rule-Based Publishing States
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Solution Overview
Problem
Conventional data platforms face challenges in managing versioning and metadata integration across multiple data distribution types, leading to friction in data access and editing for multiple collaborators, and require manual document re-drafting for changes.
Innovation Solution
A system and method that analyzes data offerings based on predefined rules, shifts them to a publishable state, and facilitates seamless transitions of updated content, enabling frictionless access and integration across various data platforms.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If all materials are created as drafts requiring manual re-drafting for changes, then version control is simplified, but collaboration efficiency deteriorates and time is lost
Solution Approach 1:
The system performs preliminary actions by automatically creating draft versions of data offerings before they are published. The draft creation process includes pre-populating metadata, validating data properties against predefined rules, and preparing the content for review, thereby eliminating the need for manual re-drafting while maintaining version control simplicity.
Solution Approach 2:
The system enables self-service by allowing data owners to automatically publish updated data offerings without requiring manual intervention for each change. The automated publishing process uses predefined rules to validate and transition drafts to published versions, reducing time loss while maintaining controlled versioning.
2Ease of operation
If multiple collaborators edit documents externally before publishing, then editing flexibility is improved, but workflow complexity increases and coordination becomes difficult
Solution Approach 1:
The system merges multiple editing operations into a single unified workflow. Instead of requiring collaborators to edit externally and then manually integrate changes, the system combines all edits into a single draft version that is automatically validated and published, simplifying the workflow while maintaining editing flexibility through the user interface.
Solution Approach 2:
The system introduces an intermediary layer in the form of an automated validation and transition system. This intermediary processes draft versions, validates them against predefined rules, and manages the transition to published versions, thereby simplifying the workflow complexity while allowing multiple collaborators to edit flexibly.
3Adaptability or versatility
If metadata is managed across multiple data distribution types, then adaptability is improved, but system complexity increases and integration becomes difficult
Solution Approach 1:
The system implements universality by creating a single unified metadata management framework that handles multiple data distribution types (e.g., Python, Snowflake, etc.) through a common set of predefined rules. The system validates and manages metadata for different distribution types using the same core mechanisms, thereby supporting adaptability without proportionally increasing complexity.
Solution Approach 2:
The system manages parameter changes by using predefined rules that define acceptable metadata properties for different data distribution types. When metadata is updated, the system automatically validates changes against these rules and transitions the data offering through controlled states, thereby managing complexity through standardized parameter validation rather than custom integration logic for each distribution type.
4Productivity
If automated publishing is implemented, then productivity is improved, but control over publication timing and status management becomes more complex
Solution Approach 1:
The system implements dynamics by creating a flexible state management framework that automatically transitions data offerings through different statuses (draft, review, published) based on predefined conditions. The system dynamically adjusts publication timing and status management based on the data offering's current state and the changes made, thereby improving productivity while managing complexity through automated state transitions rather than manual status control.
Data Source
AI summary
A method and a system for managing data offerings are provided. The method includes: receiving a first data offering that is in a first administrative state that is only viewable to a data owner of the first data offering; analyzing a series of rules relating to at least one data property of the first data offering; determining, based on a result of the analyzing of the series of rules, a current status of the first data offering; shifting the first data offering from being in the first administrative state to a second administrative state based on whether the current status is in a predetermined status; receiving, via the user interface, a first request to publish the first data offering; and publishing, in response to the first request and the first data offering being in the second administrative state, the first data offering.