BOOKS - Data-Driven Modelling and Predictive Analytics in Business and Finance
Data-Driven Modelling and Predictive Analytics in Business and Finance - Alex Khang, Rashmi Gujrati, Hayri Uygun, R.K. Tailor, Sanjaya Singh Gaur 2025 PDF CRC Press BOOKS
ECO~18 kg CO²

1 TON

Views
60037

Telegram
 
Data-Driven Modelling and Predictive Analytics in Business and Finance
Author: Alex Khang, Rashmi Gujrati, Hayri Uygun, R.K. Tailor, Sanjaya Singh Gaur
Year: 2025
Pages: 443
Format: PDF
File size: 18.9 MB
Language: ENG



Pay with Telegram STARS
Datadriven Modelling and Predictive Analytics in Business and Finance In today's fast-paced digital world, technology is constantly evolving, and it is crucial to stay up-to-date with the latest advancements in order to remain competitive in business and finance. One such area that has seen significant growth in recent years is datadriven modelling and predictive analytics. These next-generation technologies have the potential to revolutionize the way we conduct transactions in finance, banking, and business, enabling intelligent computing and modern business systems. However, the power and consistency of datadriven competencies pose a critical challenge, as does developing explainable AI (XAI) to make datadriven transactions transparent. Data analytics is at the core of datadriven modelling and predictive analytics, and it involves examining, cleaning, transforming, and interpreting data to uncover meaningful patterns, trends, and insights.
Datadriven Modeling and Predictive Analytics in Business and Finance В современном быстро развивающемся цифровом мире технологии постоянно развиваются, и крайне важно быть в курсе последних достижений, чтобы оставаться конкурентоспособными в бизнесе и финансах. Одной из таких областей, в которой наблюдается значительный рост в последние годы, является моделирование на основе данных и прогнозная аналитика. Эти технологии нового поколения способны революционизировать способы проведения транзакций в сфере финансов, банковского дела и бизнеса, обеспечивая интеллектуальные вычисления и современные бизнес-системы. Однако мощность и согласованность компетенций, управляемых данными, представляют собой критическую проблему, как и разработка объяснимого искусственного интеллекта (XAI) для обеспечения прозрачности транзакций, управляемых данными. Анализ данных лежит в основе управляемого данными моделирования и прогнозного анализа и включает в себя изучение, очистку, преобразование и интерпретацию данных для выявления значимых закономерностей, тенденций и идей.
Datadriven Modeling and Predictive Analytics in Business and Finance Dans le monde numérique en évolution rapide d'aujourd'hui, la technologie est en constante évolution et il est essentiel de se tenir au courant des dernières avancées pour rester compétitif dans les affaires et la finance. L'un de ces domaines, qui a connu une forte croissance ces dernières années, est la modélisation fondée sur les données et l'analyse prédictive. Ces technologies de nouvelle génération peuvent révolutionner les transactions financières, bancaires et commerciales en fournissant des systèmes informatiques intelligents et des systèmes d'affaires modernes. Cependant, la puissance et la cohérence des compétences gérées par les données constituent un défi majeur, tout comme le développement de l'intelligence artificielle explicable (IA's) pour assurer la transparence des transactions gérées par les données. L'analyse des données est au cœur de la modélisation et de l'analyse prédictive guidée par les données et comprend l'étude, le nettoyage, la transformation et l'interprétation des données pour identifier des schémas, des tendances et des idées significatifs.
Datadriven Modeling and Predictive Analytics in Business and Finance En el mundo digital en rápida evolución, la tecnología está en constante evolución y es fundamental estar al tanto de los últimos avances para seguir siendo competitivos en negocios y finanzas. Una de estas áreas, que ha experimentado un crecimiento significativo en los últimos , es la simulación basada en datos y el análisis predictivo. Estas tecnologías de nueva generación son capaces de revolucionar las formas en que se realizan las transacciones en los sectores financiero, bancario y empresarial, proporcionando computación inteligente y sistemas empresariales modernos. n embargo, la potencia y coherencia de las competencias gestionadas por los datos suponen un reto crítico, al igual que el desarrollo de la Inteligencia Artificial Explicable (XAI) para garantizar la transparencia de las transacciones gestionadas por los datos. análisis de datos es la base de la simulación y el análisis predictivo gestionados por datos e incluye el estudio, la depuración, la transformación y la interpretación de datos para identificar patrones, tendencias e ideas significativas.
Datadriven Modeling and Predictive Analytics in Business and Finance In un mondo digitale in continua evoluzione, la tecnologia è in continua evoluzione ed è fondamentale essere consapevoli dei recenti progressi per rimanere competitivi nel business e nella finanza. Una di queste aree in cui si è registrato un notevole aumento negli ultimi anni è stata la simulazione basata sui dati e l'analisi delle previsioni. Queste tecnologie di nuova generazione sono in grado di rivoluzionare le modalità di transazione delle attività finanziarie, bancarie e aziendali, fornendo elaborazione intelligente e sistemi aziendali avanzati. Tuttavia, la potenza e la coerenza delle competenze gestite dai dati rappresentano un problema critico, proprio come lo sviluppo di un'intelligenza artificiale spiegabile (XAI) per garantire la trasparenza delle transazioni gestite dai dati. L'analisi dei dati è alla base dei dati di simulazione e di analisi di previsione e comprende lo studio, la pulizia, la conversione e l'interpretazione dei dati per individuare modelli, tendenze e idee importanti.
Datadriven Modellierung und Predictive Analytics in Wirtschaft und Finanzen In der heutigen schnelllebigen digitalen Welt entwickelt sich die Technologie ständig weiter und es ist entscheidend, auf dem neuesten Stand zu bleiben, um in Wirtschaft und Finanzen wettbewerbsfähig zu bleiben. Ein solcher Bereich, der in den letzten Jahren ein deutliches Wachstum verzeichnet hat, ist die datenbasierte Modellierung und Predictive Analytics. Diese Technologien der nächsten Generation haben das Potenzial, die Art und Weise, wie Transaktionen in den Bereichen Finanzen, Banken und Unternehmen durchgeführt werden, zu revolutionieren, indem sie intelligentes Computing und moderne Geschäftssysteme ermöglichen. Die Macht und Konsistenz datengetriebener Kompetenzen stellt jedoch eine kritische Herausforderung dar, ebenso wie die Entwicklung erklärbarer künstlicher Intelligenz (XAI), um datengetriebene Transaktionen transparent zu machen. Die Datenanalyse ist das Herzstück der datengesteuerten Modellierung und prädiktiven Analyse und umfasst die Untersuchung, Bereinigung, Umwandlung und Interpretation von Daten, um sinnvolle Muster, Trends und Ideen zu identifizieren.
Datadriven Modeling and Predictive Analytics in Business and Finance W dzisiejszym szybko rozwijającym się świecie cyfrowym technologia stale się rozwija i kluczowe jest, aby śledzić najnowsze osiągnięcia, aby pozostać konkurencyjnym w biznesie i finansach. Jednym z takich obszarów, który odnotował znaczny wzrost w ostatnich latach, jest modelowanie oparte na danych i analiza prognostyczna. Te technologie nowej generacji mogą zrewolucjonizować sposób, w jaki dokonujesz transakcji w finansach, bankowości i biznesie, umożliwiając inteligentne obliczenia i zaawansowane systemy biznesowe. ła i spójność kompetencji opartych na danych są jednak kluczowym wyzwaniem, podobnie jak rozwój zrozumiałej sztucznej inteligencji (XAI) w celu zapewnienia przejrzystości transakcji opartych na danych. Analiza danych stanowi podstawę modelowania i analizy predykcyjnej opartej na danych oraz polega na badaniu, czyszczeniu, przekształcaniu i interpretacji danych w celu zidentyfikowania znaczących wzorców, trendów i pomysłów.
''
İş ve Finansta Datadriven Modelleme ve Öngörücü Analitik Günümüzün hızlı dijital dünyasında, teknoloji sürekli gelişmektedir ve iş ve finans alanında rekabetçi kalabilmek için en son gelişmelerden haberdar olmak çok önemlidir. Son yıllarda önemli bir büyüme gösteren bu alanlardan biri veri odaklı modelleme ve tahmine dayalı analitiktir. Bu yeni nesil teknolojiler, finans, bankacılık ve iş dünyasında işlem yapma biçiminizde devrim yaratabilir, akıllı bilgi işlem ve gelişmiş iş sistemleri sağlar. Bununla birlikte, veriye dayalı yetkinliklerin gücü ve tutarlılığı, veriye dayalı işlemlerin şeffaflığını sağlamak için açıklanabilir yapay zekanın (XAI) geliştirilmesi gibi kritik bir zorluktur. Veri analizi, veri odaklı modelleme ve öngörücü analizin temelini oluşturur ve anlamlı kalıpları, eğilimleri ve fikirleri tanımlamak için verileri incelemeyi, temizlemeyi, dönüştürmeyi ve yorumlamayı içerir.
Datadriven النمذجة والتحليلات التنبؤية في الأعمال والتمويل في عالم اليوم الرقمي سريع الخطى، تتطور التكنولوجيا باستمرار، ومن الأهمية بمكان مواكبة أحدث التطورات من أجل الحفاظ على قدرتها التنافسية في مجال الأعمال والتمويل. أحد هذه المجالات التي شهدت نموًا كبيرًا في السنوات الأخيرة هو النمذجة القائمة على البيانات والتحليلات التنبؤية. يمكن أن تحدث هذه التقنيات من الجيل التالي ثورة في الطريقة التي تتعامل بها في التمويل والخدمات المصرفية والأعمال، مما يتيح الحوسبة الذكية وأنظمة الأعمال المتقدمة. ومع ذلك، فإن قوة واتساق الكفاءات القائمة على البيانات يمثل تحديًا خطيرًا، وكذلك تطوير ذكاء اصطناعي قابل للتفسير (XAI) لضمان شفافية المعاملات القائمة على البيانات. يقوم تحليل البيانات على النمذجة القائمة على البيانات والتحليل التنبؤي ويتضمن فحص البيانات وتنظيفها وتحويلها وتفسيرها لتحديد الأنماط والاتجاهات والأفكار ذات المغزى.
商業和金融中的數據化建模和預測分析在當今快速發展的數字世界中,技術不斷發展,必須跟上最新進展,以保持商業和金融競爭力。近來增長顯著的領域之一是基於數據的建模和預測分析。這些新一代技術能夠徹底改變金融、銀行和商業交易的方式,提供智能計算和現代商業系統。但是,數據驅動能力的力量和一致性是一個關鍵問題,開發可解釋的人工智能(XAI)以確保數據驅動交易的透明度也是如此。數據分析是數據驅動的建模和預測分析的核心,涉及數據的研究,清理,轉換和解釋,以確定有意義的模式,趨勢和想法。

You may also be interested in:

Advanced Analytics with Transact-SQL: Exploring Hidden Patterns and Rules in Your Data
Green Computing for Sustainable Smart Cities A Data Analytics Applications Perspective
Machine Learning for Civil and Environmental Engineers A Practical Approach to Data-driven Analysis, Explainability, and Causality
The Family Firm: A Data-Driven Guide to Better Decision Making in the Early School Years (The ParentData Series)
Machine Learning for Civil and Environmental Engineers: A Practical Approach to Data-Driven Analysis, Explainability, and Causality
CRC Handbook of Basic Tables for Chemical Analysis Data-Driven Methods and Interpretation, Fourth Edition
Statistics 101 From Data Analysis and Predictive Modeling to Measuring Distribution and Determining Probability, Your Essential Guide to Statistics (Adams 101)
Machine Learning in Python for Dynamic Process Systems A practitioner’s guide for building process modeling, predictive, and monitoring solutions using dynamic data
Machine Learning in Python for Dynamic Process Systems A practitioner’s guide for building process modeling, predictive, and monitoring solutions using dynamic data
Management in the Era of Big data Issues and Challenges (Data Analytics Applications)
No-Code Data Science Mastering Advanced Analytics, Machine Learning, and Artificial Intelligence
Health Analytics with R Learning Data Science Using Examples from Healthcare and Direct-to-Consumer Genetics
Football Analytics with Python & R Learning Data Science Through the Lens of Sports (Final)
No-Code Data Science Mastering Advanced Analytics, Machine Learning, and Artificial Intelligence
Data Mining for Business Analytics Concepts, Techniques, and Applications with XLMiner, 3rd Edition
Amazon Redshift The Definitive Guide Jump-Start Analytics Using Cloud Data Warehousing
The Analytics Revolution in Higher Education: Big Data, Organizational Learning, and Student Success
Football Analytics with Python & R Learning Data Science Through the Lens of Sports (Final)
AWS Certified Data Analytics Study Guide Specialty (DAS-C01) Exam
Advanced Metaheuristic Methods in Big Data Retrieval and Analytics (Advances in Computational Intelligence and Robotics)
Product Analytics Applied Data Science Techniques for Actionable Consumer Insights (Rough Cuts)
Machine Learning Cookbook with Python Create ML and Data Analytics Projects Using Some Amazing Open Datasets
Google BigQuery The Definitive Guide Data Warehousing, Analytics, and Machine Learning at Scale, First Edition
Learn Microsoft Fabric: A practical guide to performing data analytics in the era of artificial intelligence
Data Analytics for Discourse Analysis with Python: The Case of Therapy Talk (Routledge Studies in Linguistics)
Extending Excel with Python and R: Unlock the potential of analytics languages for advanced data manipulation and visualization
Graph-Powered Analytics and Machine Learning with TigerGraph: Driving Business Outcomes with Connected Data
Planning and Reporting in BI-supported Controlling: Fundamentals, Business Intelligence, Mobile BI, Big Data Analytics and AI
Deciphering Data Architectures Choosing Between a Modern Data Warehouse, Data Fabric, Data Lakehouse, and Data Mesh
Deciphering Data Architectures Choosing Between a Modern Data Warehouse, Data Fabric, Data Lakehouse, and Data Mesh
Multimedia-enabled Sensors in IoT Data Delivery and Traffic Modelling
The Application of Airborne Lidar Data in the Modelling of 3D Urban Landscape Ecology
Cyber-Physical Systems Data Science, Modelling and Software Optimization
Innovations in Data Analytics: Selected Papers of ICIDA 2022 (Advances in Intelligent Systems and Computing, 1442)
Proceedings of Data Analytics and Management: ICDAM 2022 (Lecture Notes in Networks and Systems Book 572)
Applied Data Analytics - Principles and Applications (River Publishers Series in Signal, Image and Speech Processing)
Google Analytics and GA4: Improve your online sales by better understanding customer data and how customers interact with your website
Data Science and Risk Analytics in Finance and Insurance (Chapman and Hall CRC Financial Mathematics Series)
Python for Beginners A Step by Step Guide to Python Programming, Data Science, and Predictive Model. A Practical Introduction to Machine Learning with Python
Advanced Analytics with Power BI and Excel Learn Powerful Visualization and Data Analysis Techniques Using Microsoft BI Tools along with Python and R