BOOKS - OS AND DB - Data Quality Engineering in Financial Services Applying Manufactu...
Data Quality Engineering in Financial Services Applying Manufacturing Techniques to Data - Brian Buzzelli 2022 EPUB O’Reilly Media BOOKS OS AND DB
ECO~18 kg CO²

1 TON

Views
765619

Telegram
 
Data Quality Engineering in Financial Services Applying Manufacturing Techniques to Data
Author: Brian Buzzelli
Year: 2022
Pages: 470
Format: EPUB
File size: 10 MB
Language: ENG



Book Description: Data Quality Engineering in Financial Services: Applying Manufacturing Techniques to Data Author: Brian Buzzelli 2022 470 O’Reilly Media Summary: In today's fast-paced digital world, data quality plays a critical role in determining the success or failure of financial services organizations. With the increasing use of advanced technologies, the importance of data quality has become even more pronounced. This book "Data Quality Engineering in Financial Services: Applying Manufacturing Techniques to Data" by Brian Buzzelli provides a comprehensive guide to understanding the significance of data quality and its impact on the financial sector. The author emphasizes the need for data analysts, data scientists, and other data practitioners to adopt manufacturing techniques to ensure precise data quality tolerances at the datum level. The book begins with an introduction to the concept of data quality engineering and its relevance to the financial industry. It highlights the consequences of poor data quality, such as missed opportunities, lost clients, and financial disasters. The author then delves into the principles of manufacturing techniques and their application to data management. The book covers the following topics: 1.
Data Quality Engineering in Financial Services: Applying Manufacturing Techniques to Data Author: Brian Buzzelli 2022 470 O'Reilly Media Резюме: В современном быстро развивающемся цифровом мире качество данных играет решающую роль в определении успеха или провала организаций, предоставляющих финансовые услуги. С ростом использования передовых технологий важность качества данных стала еще более выраженной. В этой книге Брайана Буццелли «Data Quality Engineering in Financial Services: Applying Manufacturing Techniques to Data» приводится исчерпывающее руководство по пониманию значимости качества данных и его влияния на финансовый сектор. Автор подчеркивает необходимость для аналитиков данных, специалистов по анализу данных и других специалистов по обработке данных применять методы производства для обеспечения точных допусков качества данных на уровне базы данных. Книга начинается с введения в концепцию инженерии качества данных и ее актуальности для финансовой отрасли. В нем освещаются последствия низкого качества данных, такие как упущенные возможности, потерянные клиенты и финансовые катастрофы. Затем автор углубляется в принципы производственных методик и их применение к управлению данными. Книга охватывает следующие темы: 1.
Data Quality Engineering in Financial Services: Applying Manufacturing Techniques to Data Author: Brian Buzzelli 2022 470 O'Reilly Media Resumen: En el mundo digital en rápida evolución, la calidad de los datos es fundamental para determinar el éxito o el fracaso de las organizaciones de servicios financieros. Con el creciente uso de tecnologías avanzadas, la importancia de la calidad de los datos se ha vuelto aún más pronunciada. Este libro de Brian Buzzelli, «Data Quality Engineering in Financial Services: Applying Manufacturing Techniques to Data», proporciona una guía exhaustiva para entender la importancia de la calidad de los datos y su impacto en el sector financiero. autor subraya la necesidad de que los analistas de datos, los analistas de datos y otros procesadores de datos apliquen métodos de producción para garantizar tolerancias precisas de la calidad de los datos a nivel de la base de datos. libro comienza con una introducción al concepto de ingeniería de calidad de datos y su relevancia para la industria financiera. Destaca los efectos de la mala calidad de los datos, como las oportunidades perdidas, los clientes perdidos y los desastres financieros. A continuación, el autor profundiza en los principios de las técnicas de producción y su aplicación a la gestión de datos. libro cubre los siguientes temas: 1.
''
金融サービスにおけるデータ品質エンジニアリング:製造技術をデータに適用する著者:Brian Buzzelli 2022 470 O'Reilly Media要約:今日急速に進化するデジタル世界では、データ品質は金融サービス組織の成功または失敗を決定する上で重要な役割を果たしています。高度な技術の使用が増加するにつれて、データ品質の重要性はさらに顕著になりました。Brian Buzzelliによる「金融サービスにおけるデータ品質エンジニアリング:製造技術をデータに適用する」という本は、データ品質の重要性と金融セクターへの影響を理解するための包括的なガイドを提供しています。著者は、データアナリスト、データサイエンティスト、その他のデータサイエンティストが、データベースレベルで正確なデータ品質公差を確保するために製造技術を適用する必要性を強調しています。本書は、データ品質工学の概念と金融業界との関連性の紹介から始まります。これは、機会を逃した、顧客を失った、金融災害などのデータ品質の低下の結果を強調しています。それから著者はデータ管理への生産方法そして適用の原則を掘り下げます。本は次のトピックをカバーしています:1。

You may also be interested in:

Data Quality Engineering in Financial Services Applying Manufacturing Techniques to Data
Financial Data Engineering Design and Build Data-Driven Financial Products
Financial Data Engineering Design and Build Data-Driven Financial Products
Data-Centric Machine Learning with Python: The ultimate guide to engineering and deploying high-quality models based on good data
Practical Data Analytics for BFSI Leveraging Data Science for Driving Decisions in Banking, Financial Services, and Insurance Operations
End-to-End Quality of Service over Cellular Networks Data Services Performance Optimization in 2G/3G
Ultimate Data Engineering with Databricks Develop Scalable Data Pipelines Using Data Engineering|s Core Tenets Such as Delta Tables, Ingestion, Transformation, Security, and Scalability
Ultimate Data Engineering with Databricks Develop Scalable Data Pipelines Using Data Engineering|s Core Tenets Such as Delta Tables, Ingestion, Transformation, Security, and Scalability
A First Course in Quality Engineering Integrating Statistical and Management Methods of Quality, Third Edition
Ultimate Azure Data Engineering Build Robust Data Engineering Systems on Azure with SQL, ETL, Data Modeling, and Power BI for Business Insights and Crack Azure Certifications
Ultimate Azure Data Engineering Build Robust Data Engineering Systems on Azure with SQL, ETL, Data Modeling, and Power BI for Business Insights and Crack Azure Certifications
Data Engineering Design Patterns Recipes for Solving the Most Common Data Engineering Problems (3rd Early Release)
Data Engineering Design Patterns Recipes for Solving the Most Common Data Engineering Problems (3rd Early Release)
Advanced Data Analytics with AWS Explore Data Analysis Concepts in the Cloud to Gain Meaningful Insights and Build Robust Data Engineering Workflows Across Diverse Data Sources
Advanced Data Analytics with AWS Explore Data Analysis Concepts in the Cloud to Gain Meaningful Insights and Build Robust Data Engineering Workflows Across Diverse Data Sources
Modernizing Financial Regulation (Financial Institutuions and Services)
Advanced Data Analytics with AWS: Explore Data Analysis Concepts in the Cloud to Gain Meaningful Insights and Build Robust Data Engineering Workflows Across Diverse Data Sources (English Edition)
Fuzzy Data Matching with SQL Enhancing Data Quality and Query Performance
Automating Data Quality Monitoring: Going Deeper Than Data Observability
Azure Data Engineering Cookbook: Get well versed in various data engineering techniques in Azure using this recipe-based guide, 2nd Edition
Practical Python Data Wrangling and Data Quality
Getting Started with DuckDB: A practical guide for accelerating your data science, data analytics, and data engineering workflows
Streaming Data Mesh: A Model for Optimizing Real-Time Data Services
Data as a Service A Framework for Providing Reusable Enterprise Data Services
Simulating Conversations for the Prediction of Speech Quality (T-Labs Series in Telecommunication Services)
Practical Data Science with Jupyter Explore Data Cleaning, Pre-processing, Data Wrangling, Feature Engineering and Machine Learning using Python and Jupyter
A Guide to Software Quality Engineering
A Guide to Software Quality Engineering
A Proposed Framework for Integration of Quality Performance Measures for Health Literacy, Cultural Competence, and Language Access Services: Proceedings of a Workshop
Financial Markets and Services
Data Quality Fundamentals
Data Quality Fundamentals
Data Engineering with AWS: A Comprehensive Guide to Building Robust Data Pipelines
Data in Context: Models as Enablers for Managing and Using Data (The Enterprise Engineering Series)
Fundamentals of Data Engineering: Plan and Build Robust Data Systems
Total Quality Management in Human Service Organizations (SAGE Human Services Guides)
Reliability Engineering and Services
Hands on Azure Data Studio Microsoft|s Open Platform for Data Engineering and Analytics
Artificial Intelligence in the Financial Services Industry