AI-Enabled HUMAN CAPITAL Workday Analytics Powered by Snowflake Cortex

# **Overview**

The Dataplatr People Analytics Accelerator for Workday HR is delivered as a Snowflake Data Share — a ready-to-consume, AI-ready analytical foundation built natively on the Snowflake Data Cloud. It bridges the gap between complex Workday HR data and actionable workforce intelligence through two high-fidelity semantic views: HC Headcount and HC Terminated.

Snowflake Semantic Views capture the metadata required for consistent and accurate AI-powered analytics, such as synonyms, sample values, and verified queries. These semantic views translate raw Workday HRIS, HRMS, HR tables into structured, self-describing models that Snowflake Cortex Analyst can navigate using natural language — enabling HR, Finance, and People Operations teams to query headcount trends, termination analysis, manager hierarchy drill-downs, and workforce breakdowns without writing a single line of SQL.

The two semantic views each serve a distinct analytical purpose — monthly point-in-time snapshots for trend analysis and org hierarchy reporting, and current employee detail for active headcount KPIs, compensation analytics, and termination pattern analysis — providing complete People Analytics coverage in a single, unified data share.

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# Business Use Cases

**Example 1 -** <br/>“*Give me the total active headcount for the most recent snapshot month broken down by business unit. Then show me the full org hierarchy under Michael Anderson — I want to see headcount at each manager level from level 8 down to level 2. Finish with a bar chart showing headcount by business unit.*”

**Example 2 -** <br/>“*Show me the month-on-month headcount trend for 2025, split by event type — Active, Hire, and Termination. I want to understand if we are growing or shrinking each month. Also break down the new hires by business unit for the same period. Conclude with a stacked bar chart showing all three event types by snapshot month.*”

**Example 3 -** <br/>“*Give me a breakdown of all terminations for the current year. Show me the monthly termination count by business unit, the top termination reasons, and the voluntary vs involuntary split. I also want to see the terminated headcount by job title. Finish with a bar chart for monthly terminations by business unit and a donut chart showing termination reasons.*”

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# **Why Choose the Dataplatr People Analytics Accelerator**

## **HR-Aware Data Architecture**

The Workday People Analytics semantic views are built on a specialised foundation for complex Workday HR data. They deliver a high-fidelity schema that inherently reflects the structure of employee snapshots, manager hierarchies, termination categories, and compensation data — ensuring the data is AI-ready for immediate use within the Snowflake ecosystem.

## **Seamless Integration & Bespoke Customisation**

Dataplatr specialises in tailoring these data assets to your specific Workday environment. We excel at extending the People Analytics views with external silos — such as Payroll, Performance Management, or Recruiting — to create a unified, 360-degree workforce view. This schema can be customised by Dataplatr to align with your unique HR reporting requirements and organisational hierarchy.

## **AI-First Design for Snowflake Cortex**

The People Analytics semantic views provide the semantic clarity needed for Snowflake Cortex Analyst to accurately navigate workforce data. Our configuration-driven design allows for the addition of new dimensions or tables without heavy data engineering. Dataplatr can further extend this foundation to include Learning & Development, Talent Acquisition, and Compensation benchmarking.

## **End-to-End Workforce Visibility**

These semantic views provide the clean, structured foundation required for a connected view of the entire people function. The architecture supports integration across Finance, Payroll, and Recruiting — providing the transparency necessary for enterprise-wide workforce automation and talent control.

## **The Dataplatr Advantage**

The Dataplatr People Analytics Accelerator provides a ready-to-deploy, AI-ready foundation on Snowflake. By combining ELT automation with Dataplatr's deep expertise in Workday HR customisation, we help enterprises modernise workforce analytics and achieve faster time-to-insight. Whether you are analysing attrition patterns across business units or benchmarking headcount growth quarter over quarter, Dataplatr ensures your people data is clean, connected, and intelligent.

Contact us at: [e-mail]<br/>For consultations or custom inquiries: [https://dataplatr.com/contact-us<br/>](https://dataplatr.com/contact-us)[Linkedin](https://www.linkedin.com/company/dataplatrinc)

原始信息汇总

AI-Enabled HUMAN CAPITAL Workday Analytics Powered by Snowflake Cortex 数据集概述

数据集基本信息

• 数据集名称: AI-Enabled HUMAN CAPITAL Workday Analytics Powered by Snowflake Cortex
• 提供商: Dataplatr Corp
• 获取方式: 免费试用
• 试用期: 30天

数据集概述

Dataplatr People Analytics Accelerator for Workday HR 以 Snowflake Data Share 形式交付，是一个原生构建于 Snowflake Data Cloud 之上、可供直接使用且支持 AI 的现成分析基础。它通过两个高保真语义视图（HC Headcount 和 HC Terminated）弥合了复杂的 Workday HR 数据与可操作的人力情报之间的差距。

Snowflake 语义视图捕获了进行一致且准确的 AI 驱动分析所需的元数据，如同义词、样本值和已验证查询。这些语义视图将原始的 Workday HRIS、HRMS、HR 表转换为结构化、自描述模型，Snowflake Cortex Analyst 可使用自然语言进行导航，使 HR、财务和人员运营团队能够查询人员编制趋势、离职分析、管理层级下钻和人力构成，而无需编写任何 SQL 代码。

这两个语义视图各自服务于不同的分析目的：用于趋势分析和组织层级报告的月度时间点快照，以及用于活跃人员编制 KPI、薪酬分析和离职模式分析的当前员工详细信息，从而在单一、统一的数据共享中提供完整的人员分析覆盖。

业务需求与用例

业务需求

• 人员编制趋势与人力规划: 按月跟踪当年总活跃人员编制并与上一年比较；在最近月末快照中分析跨业务单元的人员编制分布；通过自动增量计算监控月度人员编制变化；从 CEO 级别到个人贡献者级别下钻管理层级。
• 招聘与流失分析: 分析当年每月按业务单元划分的新员工数量；按原因细分跟踪月度离职情况以进行根本原因分析；监控自愿与非自愿离职比例以了解流失质量；按月比较年度离职数量以识别季节性流失模式。
• 活跃人员编制 KPI 与人口统计: 监控实时 KPI 面板：活跃人员编制、离职人数、离职率、休假员工数、休假率；按职位、职位代码和销售团队对活跃人员编制进行排名；按性别细分分析分支机构与远程办公的人员编制划分；通过年龄层和性别交叉表了解员工年龄构成。
• 薪酬与人力情报: 分析活跃员工按组织的平均和总年薪；识别离职率最高的职位以指导留任投资；在单一视图中结合薪资和人员编制数据支持战略性人力规划。
• 智能分析: 自然语言 HR 查询——通过 Snowflake Cortex Analyst 用通俗英语询问有关人员编制、流失和人力构成的问题；自动呈现人员编制趋势、离职高峰或人口统计变化，无需手动分析；通过 Snowflake Cortex Analyst 交付的面向高管的现成人员分析仪表板；KPI 报告：活跃人员编制、流失率和薪酬分析集成于单一对话界面。

业务用例示例

1. 提供最近快照月份按业务单元细分的总活跃人员编制。然后显示 Michael Anderson 下的完整组织层级——我想查看从 8 级到 2 级每个管理层级的人员编制。最后用条形图显示按业务单元划分的人员编制。
2. 显示 2025 年按月划分的人员编制趋势，按事件类型（活跃、招聘、离职）拆分。我想了解我们每个月是在增长还是收缩。同时按业务单元细分同期的新员工。最后用堆叠条形图显示按快照月份划分的所有三种事件类型。
3. 提供当年所有离职情况的细分。显示按业务单元划分的月度离职数量、主要离职原因以及自愿与非自愿离职比例。我还想查看按职位划分的离职人员编制。最后用条形图显示按业务单元划分的月度离职情况，并用环形图显示离职原因。

数据字典（部分列表示例）

表: EMPLOYEE_SNAPSHOT 表: WORKDAY_EMPLOYEES

名称	类型	描述
ACTIVE_STATUS	Number
ADDED_BY	Varchar
ASSIGNED_HIRING_MANAGER	Varchar
ATHLETIC_PANT_SIZE	Varchar
BONUS_PLAN_DETAILS	Varchar
BUSINESS_SITE	Varchar
BUSINESS_SITE_NAME	Varchar
BUSINESS_TITLE	Varchar
BUSINESS_UNIT_NAME	Varchar
BU_CODE	Varchar
（查看更多列）

使用示例（SQL查询）

示例 1: 查询当年每月的总活跃人员编制

sql SELECT snapshot_date, COUNT(*) AS total_headcount FROM WORKDAY_PEOPLE.EMPLOYEE_SNAPSHOT WHERE event_type = ACTIVE AND YEAR(snapshot_date) = YEAR(CURRENT_DATE) GROUP BY snapshot_date ORDER BY snapshot_date

示例 2: 查询最近快照中按业务单元划分的人员编制细分

sql SELECT bu_code, COUNT(*) AS headcount FROM WORKDAY_PEOPLE.EMPLOYEE_SNAPSHOT WHERE event_type = ACTIVE AND snapshot_date = ( SELECT MAX(snapshot_date) FROM WORKDAY_PEOPLE.EMPLOYEE_SNAPSHOT WHERE event_type = ACTIVE ) GROUP BY bu_code ORDER BY headcount DESC

示例 3: 查询最新快照中每位高层管理人员下的人员编制

sql SELECT manager_level_08, manager_level_07, manager_level_06, manager_level_05, manager_level_04, manager_level_03, manager_level_02, name, COUNT(*) AS headcount FROM WORKDAY_PEOPLE.EMPLOYEE_SNAPSHOT WHERE event_type = ACTIVE AND snapshot_date = ( SELECT MAX(snapshot_date) FROM WORKDAY_PEOPLE.EMPLOYEE_SNAPSHOT WHERE event_type = ACTIVE ) GROUP BY manager_level_08, manager_level_07, manager_level_06, manager_level_05, manager_level_04, manager_level_03, manager_level_02, name ORDER BY headcount DESC

示例 4: 查询总体人员编制 KPI（活跃、休假、离职人数及比率）

sql SELECT SUM( CASE WHEN position_status = Active THEN 1 ELSE 0 END ) AS active_employees, SUM( CASE WHEN position_status = On Leave THEN 1 ELSE 0 END ) AS on_leave, SUM( CASE WHEN position_status = Terminated THEN 1 ELSE 0 END ) AS terminated_employees, COUNT() AS total_employees, ROUND( 100.0 * SUM( CASE WHEN position_status = Terminated THEN 1 ELSE 0 END ) / NULLIF(COUNT(), 0), 2 ) AS terminated_pct, ROUND( 100.0 * SUM( CASE WHEN position_status = On Leave THEN 1 ...

示例 5: 查询活跃员工按组织的平均和总年薪

sql SELECT organization, COUNT(*) AS employee_count, ROUND(AVG(annual_salary), 2) AS avg_salary, SUM(annual_salary) AS total_salary FROM WORKDAY_PEOPLE.WORKDAY_EMPLOYEES WHERE position_status = Active GROUP BY organization ORDER BY total_salary DESC

示例 6: 比较今年与去年的离职数量

sql SELECT MONTH(TRY_TO_DATE(term_date)) AS month_num, SUM( CASE WHEN YEAR(TRY_TO_DATE(term_date)) = YEAR(CURRENT_DATE) THEN 1 ELSE 0 END ) AS terminations_current_year, SUM( CASE WHEN YEAR(TRY_TO_DATE(term_date)) = YEAR(CURRENT_DATE) - 1 THEN 1 ELSE 0 END ) AS terminations_prior_year, SUM( CASE WHEN YEAR(TRY_TO_DATE(term_date)) = YEAR(CURRENT_DATE) THEN 1 ELSE 0 END ) - SUM( CASE WHEN YEAR(TRY_TO_DATE(term_date)) = YEAR(CURRENT_DATE) - 1 THEN 1 ELSE 0 END ) AS yoy_change FROM WORKDAY_PEOPLE.WORKDAY_EMPLOYEES WHERE position_status = Terminated ...

技术详情

• 交付形式: Snowflake Data Share
• 数据产品类型: 静态数据产品
• 地理覆盖范围: 全球（按州）
• 云区域可用性: 支持 AWS 多个区域（例如非洲（开普敦）、亚太（雅加达）、亚太（马来西亚）、亚太（孟买）等）

提供商信息

• 提供商名称: Dataplatr Corp
• 联系方式:
  • 销售: [e-mail]
  • 支持: https://dataplatr.com/contact-us
• 提供商简介: Dataplatr Corp 专注于数据分析和 AI，为 SAP、Oracle EBS、Workday、Salesforce 等企业应用程序提供预构建数据模型，帮助企业释放数据的全部潜力。其企业数据工程加速器旨在加快数据管道、数据转换和集成的开发，节省时间和资源。