Dependency Visualization for Data Analytics Systems
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Solution Overview
Problem
In complex data analytics systems, it is challenging to visualize and identify the dependencies between datasets and analysis objects, making it difficult for users to determine how analysis objects are affected by changes to upstream datasets.
Innovation Solution
A visualization system that receives datasets and analysis objects, requests dependency information from respective services, and generates a graphical interface displaying the dependencies between datasets and analysis objects, allowing users to manipulate, filter, and reorganize the graph to identify affected downstream objects.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a data analytics system includes a plurality of datasets and analysis objects with complex dependencies, then the system can perform comprehensive data analysis, but it becomes difficult to visualize and identify dependencies between datasets and analysis objects
Solution Approach 1:
The patent introduces a visualization system as an intermediary component that receives datasets and analysis objects from the data analytics system, processes dependency information, and presents it in a graphical interface. This mediator translates complex internal dependencies into visual representations, making them detectable without adding complexity to the core analytics functionality.
Solution Approach 2:
The patent creates a visual copy or representation of the dependency relationships rather than directly manipulating the actual data structures. The graphical interface displays nodes representing datasets and analysis objects, with edges representing dependencies, allowing users to inspect relationships without affecting the underlying system complexity.
2Loss of information
If the system tracks dependencies between all datasets and analysis objects, then users can identify affected downstream objects, but the system complexity increases
Solution Approach 1:
The patent segments the dependency tracking functionality into a separate visualization system module. Instead of embedding dependency tracking throughout the entire data analytics system, it creates a distinct component that receives data from various sources (datasets, analysis objects) and processes dependency information independently, then presents it through a graphical interface.
Solution Approach 2:
The visualization system serves multiple functions: it displays dependency relationships, identifies downstream affected objects, provides filtering capabilities, and offers different visualization modes. This multi-functional approach consolidates various dependency management tasks into a single system, reducing overall complexity despite comprehensive tracking.
3Reliability
If the system provides detailed dependency information for all objects, then users can make informed decisions about changes, but the time required to process and display this information increases
Solution Approach 1:
The patent implements filtering capabilities that allow users to view only the necessary subset of dependency information rather than all possible data. Users can filter by object type, dependency direction, or specific datasets, receiving just enough information to make informed decisions without processing excessive data that would increase display time.
Solution Approach 2:
The system pre-processes and stores dependency information in a structured format, maintaining dependency graphs and relationship metadata in advance. When users query the system, the pre-computed dependency structures enable rapid retrieval and display of relevant information, reducing real-time processing delays while maintaining complete dependency tracking.
Data Source
AI summary
Techniques for visualizing dependencies in a data analytics system are described. In an embodiment, a visualization system may receive datasets and dataset dependency information for the datasets. The visualization system may receive a first type of analysis objects from a first analysis object system and dataset dependency information from an analysis object dependency service. The visualization system may receive a second type of analysis objects from a second analysis object system. The second type of analysis object may include a JSON representation of a set of operations that are applied during analysis such as a set of programming instructions. The visualization system may traverse and analyze the JSON representation to determine, for a given analysis object, one or more parent dependencies. The visualization system can then generate a graph of the datasets and analysis objects.