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Sequencing development（开发顺序）

The Palantir "levels" framework ↗ provides a map for enterprise-wide digital transformation. For a use case, the framework embodies one reasonable approach for the implementation sequence.
sequencing-development The article linked above shares a number of considerations. Most relevant to the use case implementation sequence is the importance of first establishing a data asset (1) and guided decision-making (2) - in this context, the data pipeline, ontology structure, and initial interfaces. You can then proceed into decision space expansion and enrichment, incorporating data science techniques for model-driven operational workflows.

Specifically, this means putting development effort and focus into the use case foundations:

  • a robust and efficient pipeline
  • a balanced, reflective, and practical object model
  • a flexible approach to enriching data with labels and metrics based on data science, rules, and manual approaches
  • re-usable interface components for object views and decision capture.

At the same time, you can explore and understand the integration story for model-driven feedback loops, digital twins, and chained scenario planning while recognizing that lower-level building blocks enable valuable multiplier technologies.

You should remember that these building blocks are not the entirety of your use case potential. Building a set of comprehensive views on top of an integration pipeline and ontology structure is your starting point for unlocking potential for flexible, interconnected, and data-driven operational workflows.

中文翻译

开发顺序

Palantir 的 "层级"框架 ↗ 为企业级数字化转型提供了路线图。就某个用例而言，该框架体现了一种合理的实施顺序方案。
sequencing-development 上述文章分享了许多考量因素。与用例实施顺序最相关的是，首先建立数据资产 (1) 和引导式决策 (2) 的重要性——在此背景下，即数据管道（data pipeline）、本体结构（ontology structure）和初始界面（initial interfaces）。然后，您可以进入决策空间扩展与丰富阶段，整合数据科学技术以构建模型驱动的运营工作流。

具体而言，这意味着将开发精力和重点投入到用例基础中：

  • 稳健高效的数据管道
  • 平衡、反映实际且实用的对象模型（object model）
  • 基于数据科学、规则和人工方法，灵活地通过标签和指标丰富数据
  • 用于对象视图（object views）和决策捕获（decision capture）的可复用界面组件。

同时，您可以探索并理解模型驱动反馈循环（model-driven feedback loops）、数字孪生（digital twins）和链式场景规划（chained scenario planning）的集成方案，同时认识到底层构建模块能够实现有价值的倍增技术。

请记住，这些构建模块并非您用例潜力的全部。在集成管道和本体结构之上构建一套全面的视图，是您释放灵活、互联且数据驱动的运营工作流潜力的起点。