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Data Quality In The Age Of Ai


Data Quality In The Age Of Ai
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Data Quality In The Age Of Ai


Data Quality In The Age Of Ai
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Author : Andrew Jones
language : en
Publisher: Packt Publishing Ltd
Release Date : 2024-05-24

Data Quality In The Age Of Ai written by Andrew Jones and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-05-24 with Computers categories.


Unlock the power of data with expert insights to enhance data quality, maximizing the potential of AI, and establishing a data-centric culture Key Features Gain a profound understanding of the interplay between data quality and AI Explore strategies to improve data quality with practical implementation and real-world results Acquire the skills to measure and evaluate data quality, empowering data-driven decisions Purchase of the Kindle book includes a free PDF eBook Book DescriptionAs organizations worldwide seek to revamp their data strategies to leverage AI advancements and benefit from newfound capabilities, data quality emerges as the cornerstone for success. Without high-quality data, even the most advanced AI models falter. Enter Data Quality in the Age of AI, a detailed report that illuminates the crucial role of data quality in shaping effective data strategies. Packed with actionable insights, this report highlights the critical role of data quality in your overall data strategy. It equips teams and organizations with the knowledge and tools to thrive in the evolving AI landscape, serving as a roadmap for harnessing the power of data quality, enabling them to unlock their data's full potential, leading to improved performance, reduced costs, increased revenue, and informed strategic decisions.What you will learn Discover actionable steps to establish data quality as the foundation of your data culture Enhance data quality directly at its source with effective strategies and best practices Elevate data quality standards and enhance data literacy within your organization Identify and measure data quality within the dataset Adopt a product mindset to address data quality challenges Explore emerging architectural patterns like data mesh and data contracts Assign roles, responsibilities, and incentives for data generators Gain insights from real-world case studies Who this book is for This report is for data leaders and decision-makers, including CTOs, CIOs, CISOs, CPOs, and CEOs responsible for shaping their organization's data strategy to maximize data value, especially those interested in harnessing recent AI advancements.



Mastering The Data Paradox


Mastering The Data Paradox
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Author : Nitin Seth
language : en
Publisher: Penguin Random House India Private Limited
Release Date : 2024-03-18

Mastering The Data Paradox written by Nitin Seth and has been published by Penguin Random House India Private Limited this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-03-18 with Computers categories.


There are two remarkable phenomena that are unfolding almost simultaneously. The first is the emergence of a data-first world, where data has become a central driving force, shaping industries and fueling innovation. The second is the dawn of the AI age, propelled by the advent of Generative AI, that has created the possibility to leverage the data of the world for the first time. The convergence of these two, with data as the common denominator, holds immense promise and the opportunities are boundless. This book provides us with opportunities to push our thinking, to innovate, to transform and to create a better future at all levels—individual, enterprise and the world.



Data Quality For The Information Age


Data Quality For The Information Age
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Author : Thomas C. Redman
language : en
Publisher: Artech House Publishers
Release Date : 1996

Data Quality For The Information Age written by Thomas C. Redman and has been published by Artech House Publishers this book supported file pdf, txt, epub, kindle and other format this book has been release on 1996 with Computers categories.


All aspects of data management are explored in this title, which provides detailed analyses of quality problems and their impacts, potential solutions and how they are combined to form an overall data quality program, senior management's role, and methods used to make and sustain improvements.



Data Quality


Data Quality
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Author : Prashanth Southekal
language : en
Publisher: John Wiley & Sons
Release Date : 2023-02-01

Data Quality written by Prashanth Southekal and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-02-01 with Computers categories.


Discover how to achieve business goals by relying on high-quality, robust data In Data Quality: Empowering Businesses with Analytics and AI, veteran data and analytics professional delivers a practical and hands-on discussion on how to accelerate business results using high-quality data. In the book, you’ll learn techniques to define and assess data quality, discover how to ensure that your firm’s data collection practices avoid common pitfalls and deficiencies, improve the level of data quality in the business, and guarantee that the resulting data is useful for powering high-level analytics and AI applications. The author shows you how to: Profile for data quality, including the appropriate techniques, criteria, and KPIs Identify the root causes of data quality issues in the business apart from discussing the 16 common root causes that degrade data quality in the organization. Formulate the reference architecture for data quality, including practical design patterns for remediating data quality Implement the 10 best data quality practices and the required capabilities for improving operations, compliance, and decision-making capabilities in the business An essential resource for data scientists, data analysts, business intelligence professionals, chief technology and data officers, and anyone else with a stake in collecting and using high-quality data, Data Quality: Empowering Businesses with Analytics and AI will also earn a place on the bookshelves of business leaders interested in learning more about what sets robust data apart from the rest.



Competing In The Age Of Ai


Competing In The Age Of Ai
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Author : Marco Iansiti
language : en
Publisher: Harvard Business Press
Release Date : 2020-01-07

Competing In The Age Of Ai written by Marco Iansiti and has been published by Harvard Business Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-01-07 with Business & Economics categories.


"a provocative new book" — The New York Times AI-centric organizations exhibit a new operating architecture, redefining how they create, capture, share, and deliver value. Now with a new preface that explores how the coronavirus crisis compelled organizations such as Massachusetts General Hospital, Verizon, and IKEA to transform themselves with remarkable speed, Marco Iansiti and Karim R. Lakhani show how reinventing the firm around data, analytics, and AI removes traditional constraints on scale, scope, and learning that have restricted business growth for hundreds of years. From Airbnb to Ant Financial, Microsoft to Amazon, research shows how AI-driven processes are vastly more scalable than traditional processes, allow massive scope increase, enabling companies to straddle industry boundaries, and create powerful opportunities for learning—to drive ever more accurate, complex, and sophisticated predictions. When traditional operating constraints are removed, strategy becomes a whole new game, one whose rules and likely outcomes this book will make clear. Iansiti and Lakhani: Present a framework for rethinking business and operating models Explain how "collisions" between AI-driven/digital and traditional/analog firms are reshaping competition, altering the structure of our economy, and forcing traditional companies to rearchitect their operating models Explain the opportunities and risks created by digital firms Describe the new challenges and responsibilities for the leaders of both digital and traditional firms Packed with examples—including many from the most powerful and innovative global, AI-driven competitors—and based on research in hundreds of firms across many sectors, this is your essential guide for rethinking how your firm competes and operates in the era of AI.



Management Of Data In Ai Age


Management Of Data In Ai Age
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Author : Amandeep Kaur
language : en
Publisher: CSMFL Publications
Release Date : 2020-10-10

Management Of Data In Ai Age written by Amandeep Kaur and has been published by CSMFL Publications this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-10-10 with Computers categories.


This book is a compilation of contributed works on management of data in the age of artificial intelligence. The AI technologies have changed the way the businesses do manage themselves in modern times. It becomes much more important to manage the data a business owns when the same can be collated and used by the allied AI technologies for forming business decisions. This book highlights how AI and machine learning can help businesses categorise and manage their organizational data. The book introduces how small businesses can benefit from AI technologies for their data management with limited budgets. The book advocates for making AI processes to be core part of consumer experience and support management within the businesses. As a unique feature, this book also goes to make an awareness as to how human brain can use AI’s deep learning capabilities to make reflective decisions. The book also introduces as to how big data and big data analytics can help agriculture and farm management sector. It is hoped that the readership will find this book useful in the areas of big data management, machine learning and data decisions, AI technologies for small businesses, usage of AI in emerging sectors and those areas where data needs to managed in an environment of automation.



Driving Digital Transformation Through Data And Ai


Driving Digital Transformation Through Data And Ai
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Author : Alexander Borek
language : en
Publisher: Kogan Page Publishers
Release Date : 2020-11-03

Driving Digital Transformation Through Data And Ai written by Alexander Borek and has been published by Kogan Page Publishers this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-11-03 with Computers categories.


Leading tech companies such as Netflix, Amazon and Uber use data science and machine learning at scale in their core business processes, whereas most traditional companies struggle to expand their machine learning projects beyond a small pilot scope. This book enables organizations to truly embrace the benefits of digital transformation by anchoring data and AI products at the core of their business. It provides executives with the essential tools and concepts to establish a data and AI portfolio strategy as well as the organizational setup and agile processes that are required to deliver machine learning products at scale. Key consideration is given to advancing the data architecture and governance, balancing stakeholder needs and breaking organizational silos through new ways of working. Each chapter includes templates, common pitfalls and global case studies covering industries such as insurance, fashion, consumer goods, finance, manufacturing and automotive. Covering a holistic perspective on strategy, technology, product and company culture, Driving Digital Transformation through Data and AI guides the organizational transformation required to get ahead in the age of AI.



Smarter Data Science


Smarter Data Science
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Author : Neal Fishman
language : en
Publisher: John Wiley & Sons
Release Date : 2020-04-14

Smarter Data Science written by Neal Fishman and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-04-14 with Computers categories.


Organizations can make data science a repeatable, predictable tool, which business professionals use to get more value from their data Enterprise data and AI projects are often scattershot, underbaked, siloed, and not adaptable to predictable business changes. As a result, the vast majority fail. These expensive quagmires can be avoided, and this book explains precisely how. Data science is emerging as a hands-on tool for not just data scientists, but business professionals as well. Managers, directors, IT leaders, and analysts must expand their use of data science capabilities for the organization to stay competitive. Smarter Data Science helps them achieve their enterprise-grade data projects and AI goals. It serves as a guide to building a robust and comprehensive information architecture program that enables sustainable and scalable AI deployments. When an organization manages its data effectively, its data science program becomes a fully scalable function that’s both prescriptive and repeatable. With an understanding of data science principles, practitioners are also empowered to lead their organizations in establishing and deploying viable AI. They employ the tools of machine learning, deep learning, and AI to extract greater value from data for the benefit of the enterprise. By following a ladder framework that promotes prescriptive capabilities, organizations can make data science accessible to a range of team members, democratizing data science throughout the organization. Companies that collect, organize, and analyze data can move forward to additional data science achievements: Improving time-to-value with infused AI models for common use cases Optimizing knowledge work and business processes Utilizing AI-based business intelligence and data visualization Establishing a data topology to support general or highly specialized needs Successfully completing AI projects in a predictable manner Coordinating the use of AI from any compute node. From inner edges to outer edges: cloud, fog, and mist computing When they climb the ladder presented in this book, businesspeople and data scientists alike will be able to improve and foster repeatable capabilities. They will have the knowledge to maximize their AI and data assets for the benefit of their organizations.



Unleashing The Power Of Data With Trusted Ai


Unleashing The Power Of Data With Trusted Ai
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Author : Wendy Turner-Williams
language : en
Publisher: Packt Publishing Ltd
Release Date : 2024-07-04

Unleashing The Power Of Data With Trusted Ai written by Wendy Turner-Williams and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-07-04 with Computers categories.


Discover the transformative potential of AI for data-driven decision-making and fast-track your organization's growth journey with trusted AI implementation Key Features Gain comprehensive insights and analyses to make quick and accurate decisions Learn to integrate trusted AI into your organizational workflows and decision-making processes Explore real-world case studies that showcase the transformative impact of AI in diverse industries Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionWritten by a distinguished leader and innovator who has been instrumental in spearheading digital, cloud, and AI transformations across global brands, Unleashing the Power of Data with Trusted AI is an indispensable resource that will make you AI-ready. This comprehensive guide is designed to meet the urgent need for clarity and to give you actionable insights into today's rapidly evolving landscape of AI and its fundamental driver - data. You’ll delve into the exciting world of AI and its integration with data, uncover its significance, ethical considerations, and strategic applications with real-life success stories from industry giants like Starbucks, Netflix, and Siemens. You’ll also witness first-hand how the integration of data and AI has reshaped markets and elevated customer experiences, and discover the future of generative AI based on several surveys and case studies. You’ll gain an understanding of how AI has evolved across industries, empowering decision-making and fostering innovation. Tailored for board members, executives, innovators, and tech enthusiasts, this immersive guide will reshape your understanding of data and AI synergy. By the end of this guide, you’ll be able to lead your teams, customers, partners, and organizations confidently and responsibly in the era of AI.What you will learn Navigate ethical considerations and comply with data regulations effectively Elevate data quality and enhance data literacy within your organization Craft effective AI strategies for data analytics processes Explore real-world case studies showcasing the tangible benefits of trusted AI Optimize decision-making processes by harnessing AI-driven insights Who this book is for This report is for executives and board members of mid to large enterprises, such as CDAIOs, CTOs, CIOs, CISOs, CPOs, and CEOs, as well as AI, data, ethics, privacy, and security professionals. With this book, you’ll confidently develop your data and AI implementation strategy and navigate the complex landscape of emerging technologies with clarity.



Big Data In The Age Of Ai


Big Data In The Age Of Ai
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Author :
language : en
Publisher:
Release Date : 2019

Big Data In The Age Of Ai written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019 with categories.


The hype about big data may have peaked several years ago, but big data is far from gone. Instead it forms the foundation for some of today's most exciting technologies. Artificial intelligence (AI), machine learning, and data science rely on big data, or data that-by virtue of its velocity, volume, or variety-can't be easily stored or analyzed with traditional methods. In this nontechnical course, Barton Poulson digs into the topic of big data, explaining how it works and shapes our modern data universe. Barton explains big data's relationship to AI, data science, social media, and the Internet of Things (IoT). He goes over some of the ethical issues behind the use of big data. Plus, he covers techniques involved in analyzing big data, including data mining and predictive analytics.