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

By:

Buzzelli Brian

Publication details: Shroff/O'Reilly 2022 IndiaEdition: 1stDescription: 176ISBN:

9789355423498

Subject(s):

DDC classification:

005.74015 BUZ

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 Source: https://www.amazon.in/Data-Quality-Engineering-Financial-Services/dp/9355423497/ref=sr_1_1?crid=377LT81CYVCD4&keywords=9789355423498&qid=1703236317&sprefix=9789355424150%2Caps%2C377&sr=8-1

List(s) this item appears in: New Arrivals February 2024

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Item type	Current library	Collection	Call number	Status	Date due	Barcode
Book	Main Library Analytics	Reference book	005.74015 BUZ (Browse shelf(Opens below))	Available		119111

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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

Source: https://www.amazon.in/Data-Quality-Engineering-Financial-Services/dp/9355423497/ref=sr_1_1?crid=377LT81CYVCD4&keywords=9789355423498&qid=1703236317&sprefix=9789355424150%2Caps%2C377&sr=8-1

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