Data Quality Engineering in Financial Services: Applying Manufacturing Techniques to Data

Book Description

Data quality will either make you or break you in the financial services industry. Missing prices, wrong market values, trading violations, client performance restatements, and incorrect regulatory filings can all lead to harsh penalties, lost clients, and financial disaster. This practical guide provides data analysts, data scientists, and data practitioners in financial services firms with the framework to apply manufacturing principles to financial data management, understand data dimensions, and engineer precise data quality tolerances at the datum level and integrate them into your data processing pipelines.

You’ll get invaluable advice on how to:

• Evaluate data dimensions and how they apply to different data types and use cases
• Determine data quality tolerances for your data quality specification
• Choose the points along the data processing pipeline where data quality should be assessed and measured
• Apply tailored data governance frameworks within a business or technical function or across an organization
• Precisely align data with applications and data processing pipelines
• And more

中文：

书名：金融服务中的数据质量工程: 将制造技术应用于数据

在金融服务行业，数据质量要么让你成功，要么让你崩溃。缺失的价格、错误的市场价值、交易违规、客户业绩重述以及不正确的监管文件都可能导致严厉的处罚、客户流失和金融灾难。本实用指南为金融服务公司的数据分析师，数据科学家和数据从业人员提供了将制造原理应用于金融数据管理，了解数据维度并在基准级别设计精确的数据质量容差的框架，并将其集成到您的数据处理管道中。

您将获得有关如何以下操作的宝贵建议:

• 评估数据维度以及如何应用于不同的数据类型和用例
• 根据您的数据质量规格确定数据质量容限
• 选择数据处理管道中需要评估和测量数据质量的点
• 在业务或技术部门或跨组织应用定制的数据治理框架
• 精确调整数据与应用程序和数据处理管道
• 和更多