| Description |
1 online resource |
| Summary |
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. |
| Subject |
Financial services industry -- Data processing.
|
|
Financial services industry -- Technological innovations.
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Services financiers -- Informatique. |
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Services financiers -- Innovations. |
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Financial services industry -- Data processing |
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Financial services industry -- Technological innovations |
| Other Form: |
Print version: 1098136934 9781098136932 (OCoLC)1345458333 |
| ISBN |
9781098136901 (electronic bk.) |
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109813690X (electronic bk.) |
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