Khaldy mohammad (34 risultati)

PAP. Condizione: New. New Book. Shipped from UK. Established seller since 2000.

PAP. Condizione: New. New Book. Shipped from UK. Established seller since 2000.

PAP. Condizione: New. New Book. Shipped from UK. Established seller since 2000.

Condizione: New.

Condizione: New.

Paperback. Condizione: New.

HRD. Condizione: New. New Book. Shipped from UK. Established seller since 2000.

Paperback. Condizione: New.

HRD. Condizione: New. New Book. Shipped from UK. Established seller since 2000.

Condizione: New.

HRD. Condizione: New. New Book. Shipped from UK. Established seller since 2000.

Condizione: New.

Condizione: New.

Hardback. Condizione: New.

Hardback. Condizione: New.

Condizione: As New. Unread book in perfect condition.

Paperback. Condizione: New.

Paperback. Condizione: New.

Hardback. Condizione: New.

Hardback. Condizione: New.

PAP. Condizione: New. New Book. Shipped from UK. Established seller since 2000.

HRD. Condizione: New. New Book. Shipped from UK. Established seller since 2000.

Paperback. Condizione: new. Paperback. Strategic AI integration in business intelligence (BI) transforms how organizations harness data to drive decision-making. By utilizing AI in BI systems, companies can move beyond traditional data reporting to enable predictive analytics, real-time insights, and automated decision support. This integration enhances operational efficiency and response while empowering businesses to uncover patterns, anticipate market trends, and personalize customer experiences. As AI technologies evolve, aligning them with BI frameworks becomes essential for organizations aiming to maintain a competitive edge in a data-driven marketplace. Strategic AI Integration in Business Intelligence explores how the strategic integration of artificial intelligence enhances the capabilities of business intelligence systems, enabling more advanced data analysis, automation, and decision-making. It examines the practical applications, challenges, and impacts of AI-driven BI on organizational performance and competitiveness. This book covers topics such as digital twins, machine learning, and threat detection, and is a useful resource for business owners, engineers, academicians, researchers, and data scientists. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. …

Paperback. Condizione: new. Paperback. Driving modern business intelligence (BI) architecture is essential for organizations to enhance operational efficiency and make data-driven decisions. As businesses accumulate large amounts of data from diverse sources, traditional BI tools struggle to deliver real-time insights and agility. Modern BI architecture leverages cloud-based platforms, data lakes, AI-driven analytics, and self-service capabilities to unify data access and accelerate decision-making. This empowers stakeholders across departments with actionable intelligence and streamline operations by identifying inefficiencies, predicting trends, and automating analysis. Further research into an adaptive BI framework may assist with future business strategies. Driving Modern Business Intelligence Architecture for Operational Efficiency explores the evolving landscape of data management within BI systems, addressing organizations' critical challenges in managing, processing, and utilizing vast amounts of data for strategic decision-making. It offers insights into cutting-edge tools, methodologies, and best practices for effective data management in BI environments. This book covers topics such as data governance, predictive security, and machine learning, and is a useful resource for computer engineers, business owners, economists, academicians, researchers, and data scientists. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.…

Hardcover. Condizione: new. Hardcover. Strategic AI integration in business intelligence (BI) transforms how organizations harness data to drive decision-making. By utilizing AI in BI systems, companies can move beyond traditional data reporting to enable predictive analytics, real-time insights, and automated decision support. This integration enhances operational efficiency and response while empowering businesses to uncover patterns, anticipate market trends, and personalize customer experiences. As AI technologies evolve, aligning them with BI frameworks becomes essential for organizations aiming to maintain a competitive edge in a data-driven marketplace. Strategic AI Integration in Business Intelligence explores how the strategic integration of artificial intelligence enhances the capabilities of business intelligence systems, enabling more advanced data analysis, automation, and decision-making. It examines the practical applications, challenges, and impacts of AI-driven BI on organizational performance and competitiveness. This book covers topics such as digital twins, machine learning, and threat detection, and is a useful resource for business owners, engineers, academicians, researchers, and data scientists. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. …

Hardcover. Condizione: new. Hardcover. Driving modern business intelligence (BI) architecture is essential for organizations to enhance operational efficiency and make data-driven decisions. As businesses accumulate large amounts of data from diverse sources, traditional BI tools struggle to deliver real-time insights and agility. Modern BI architecture leverages cloud-based platforms, data lakes, AI-driven analytics, and self-service capabilities to unify data access and accelerate decision-making. This empowers stakeholders across departments with actionable intelligence and streamline operations by identifying inefficiencies, predicting trends, and automating analysis. Further research into an adaptive BI framework may assist with future business strategies. Driving Modern Business Intelligence Architecture for Operational Efficiency explores the evolving landscape of data management within BI systems, addressing organizations' critical challenges in managing, processing, and utilizing vast amounts of data for strategic decision-making. It offers insights into cutting-edge tools, methodologies, and best practices for effective data management in BI environments. This book covers topics such as data governance, predictive security, and machine learning, and is a useful resource for computer engineers, business owners, economists, academicians, researchers, and data scientists. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.…

Taschenbuch. Condizione: Neu. Driving Modern Business Intelligence Architecture for Operational Efficiency | Abdelraouf Ishtaiwi (u. a.) | Taschenbuch | Englisch | 2025 | IGI Global | EAN 9798337321264 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu Print on Demand. …

Taschenbuch. Condizione: Neu. Strategic AI Integration in Business Intelligence | Abdelraouf Ishtaiwi (u. a.) | Taschenbuch | Englisch | 2025 | IGI Global | EAN 9798337368023 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu Print on Demand.…

Taschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Strategic AI integration in business intelligence (BI) transforms how organizations harness data to drive decision-making. By utilizing AI in BI systems, companies can move beyond traditional data reporting to enable predictive analytics, real-time insights, and automated decision support. This integration enhances operational efficiency and response while empowering businesses to uncover patterns, anticipate market trends, and personalize customer experiences. As AI technologies evolve, aligning them with BI frameworks becomes essential for organizations aiming to maintain a competitive edge in a data-driven marketplace. Strategic AI Integration in Business Intelligence explores how the strategic integration of artificial intelligence enhances the capabilities of business intelligence systems, enabling more advanced data analysis, automation, and decision-making. It examines the practical applications, challenges, and impacts of AI-driven BI on organizational performance and competitiveness. This book covers topics such as digital twins, machine learning, and threat detection, and is a useful resource for business owners, engineers, academicians, researchers, and data scientists.…

Taschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Driving modern business intelligence (BI) architecture is essential for organizations to enhance operational efficiency and make data-driven decisions. As businesses accumulate large amounts of data from diverse sources, traditional BI tools struggle to deliver real-time insights and agility. Modern BI architecture leverages cloud-based platforms, data lakes, AI-driven analytics, and self-service capabilities to unify data access and accelerate decision-making. This empowers stakeholders across departments with actionable intelligence and streamline operations by identifying inefficiencies, predicting trends, and automating analysis. Further research into an adaptive BI framework may assist with future business strategies. Driving Modern Business Intelligence Architecture for Operational Efficiency explores the evolving landscape of data management within BI systems, addressing organizations' critical challenges in managing, processing, and utilizing vast amounts of data for strategic decision-making. It offers insights into cutting-edge tools, methodologies, and best practices for effective data management in BI environments. This book covers topics such as data governance, predictive security, and machine learning, and is a useful resource for computer engineers, business owners, economists, academicians, researchers, and data scientists.…