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| Author | : Eswar Prasad Galla |
| Publisher | : JEC PUBLICATION |
| Total Pages | : 237 |
| Release | : |
| Genre | : Architecture |
| ISBN | : 9361758756 |
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| Author | : Bill Schmarzo |
| Publisher | : Packt Publishing Ltd |
| Total Pages | : 261 |
| Release | : 2020-11-30 |
| Genre | : Computers |
| ISBN | : 1800569130 |
Build a continuously learning and adapting organization that can extract increasing levels of business, customer and operational value from the amalgamation of data and advanced analytics such as AI and Machine Learning Key Features Master the Big Data Business Model Maturity Index methodology to transition to a value-driven organizational mindset Acquire implementable knowledge on digital transformation through 8 practical laws Explore the economics behind digital assets (data and analytics) that appreciate in value when constructed and deployed correctly Book Description In today's digital era, every organization has data, but just possessing enormous amounts of data is not a sufficient market discriminator. The Economics of Data, Analytics, and Digital Transformation aims to provide actionable insights into the real market discriminators, including an organization's data-fueled analytics products that inspire innovation, deliver insights, help make practical decisions, generate value, and produce mission success for the enterprise. The book begins by first building your mindset to be value-driven and introducing the Big Data Business Model Maturity Index, its maturity index phases, and how to navigate the index. You will explore value engineering, where you will learn how to identify key business initiatives, stakeholders, advanced analytics, data sources, and instrumentation strategies that are essential to data science success. The book will help you accelerate and optimize your company's operations through AI and machine learning. By the end of the book, you will have the tools and techniques to drive your organization's digital transformation. Here are a few words from Dr. Kirk Borne, Data Scientist and Executive Advisor at Booz Allen Hamilton, about the book: "Data analytics should first and foremost be about action and value. Consequently, the great value of this book is that it seeks to be actionable. It offers a dynamic progression of purpose-driven ignition points that you can act upon." What you will learn Train your organization to transition from being data-driven to being value-driven Navigate and master the big data business model maturity index Learn a methodology for determining the economic value of your data and analytics Understand how AI and machine learning can create analytics assets that appreciate in value the more that they are used Become aware of digital transformation misconceptions and pitfalls Create empowered and dynamic teams that fuel your organization's digital transformation Who this book is for This book is designed to benefit everyone from students who aspire to study the economic fundamentals behind data and digital transformation to established business leaders and professionals who want to learn how to leverage data and analytics to accelerate their business careers.
| Author | : John W. Foreman |
| Publisher | : John Wiley & Sons |
| Total Pages | : 432 |
| Release | : 2013-10-31 |
| Genre | : Business & Economics |
| ISBN | : 1118839862 |
Data Science gets thrown around in the press like it'smagic. Major retailers are predicting everything from when theircustomers are pregnant to when they want a new pair of ChuckTaylors. It's a brave new world where seemingly meaningless datacan be transformed into valuable insight to drive smart businessdecisions. But how does one exactly do data science? Do you have to hireone of these priests of the dark arts, the "data scientist," toextract this gold from your data? Nope. Data science is little more than using straight-forward steps toprocess raw data into actionable insight. And in DataSmart, author and data scientist John Foreman will show you howthat's done within the familiar environment of aspreadsheet. Why a spreadsheet? It's comfortable! You get to look at the dataevery step of the way, building confidence as you learn the tricksof the trade. Plus, spreadsheets are a vendor-neutral place tolearn data science without the hype. But don't let the Excel sheets fool you. This is a book forthose serious about learning the analytic techniques, the math andthe magic, behind big data. Each chapter will cover a different technique in aspreadsheet so you can follow along: Mathematical optimization, including non-linear programming andgenetic algorithms Clustering via k-means, spherical k-means, and graphmodularity Data mining in graphs, such as outlier detection Supervised AI through logistic regression, ensemble models, andbag-of-words models Forecasting, seasonal adjustments, and prediction intervalsthrough monte carlo simulation Moving from spreadsheets into the R programming language You get your hands dirty as you work alongside John through eachtechnique. But never fear, the topics are readily applicable andthe author laces humor throughout. You'll even learnwhat a dead squirrel has to do with optimization modeling, whichyou no doubt are dying to know.
| Author | : Rekha Swamy |
| Publisher | : Big Data |
| Total Pages | : 188 |
| Release | : 2019-01-20 |
| Genre | : Computers |
| ISBN | : 9781794083837 |
Data is changing the way we do business and live in our daily lives. Artificial Intelligence is replacing jobs and creating new ones at an increasing rate. Understanding what big data is and how it can be used to predict what will happen in the future is a vital skill applicable to anyone who works in IT or business that wants to be able to capitalise on the knowledge required to prosper in the future. The question and answer format at the end of each chapter assists in the process of remembering the key concepts so they can be applied at work or university. This comprehensive text book is available at a bargain price to reach a large global audience and provide readers with the opportunity to obtain a high level of understanding of the potential of data in the world. With the knowledge about the changes in business and in our daily lives you can stay ahead of the game and carve out your future.
| Author | : Merlo, Tereza Raquel |
| Publisher | : IGI Global |
| Total Pages | : 347 |
| Release | : 2024-02-07 |
| Genre | : Business & Economics |
| ISBN | : |
Within information sciences and organizational management, a pressing challenge emerges; How can we harness the transformative power of artificial intelligence (AI) and data analytics? As industries grapple with a deluge of data and the imperative to make informed decisions swiftly, the gap between data collection and actionable insights widens. Professionals in various sectors are in a race to unlock AI's full potential to drive operational efficiency, enhance decision-making, and gain a competitive edge. However, navigating this intricate terrain, laden with ethical considerations and interdisciplinary complexity, has proven to be a formidable undertaking. AI and Data Analytics Applications in Organizational Management, combines rigorous scholarship with practicality. It traverses the spectrum from theoretical foundations to real-world applications, making it indispensable for those seeking to implement AI-driven data analytics in their organizations. Moreover, it delves into the ethical and societal dimensions of this revolution, ensuring that the journey toward innovation is paved with responsible considerations. For researchers, scholars, and practitioners yearning to unleash the potential of AI in organizational management, this book is the key to not only understanding the landscape but also charting a course toward transformative change.
| Author | : Wendy Turner-Williams |
| Publisher | : Packt Publishing Ltd |
| Total Pages | : 96 |
| Release | : 2024-07-04 |
| Genre | : Computers |
| ISBN | : 1835460364 |
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.
| Author | : Phil Gilberts |
| Publisher | : Freegulls Publishing House |
| Total Pages | : 80 |
| Release | : |
| Genre | : Computers |
| ISBN | : |
Welcome to the world of data engineering, where the raw material of the digital age—data—is transformed into actionable insights that drive decisions, innovations, and advancements across industries. This book is your gateway into understanding and mastering the essential principles, practices, and technologies that underpin the field of data engineering. In today's data-driven economy, organizations increasingly rely on robust data infrastructures and efficient data pipelines to harness the power of information. Data engineering is the backbone of this infrastructure, encompassing the design, implementation, and maintenance of systems that enable the collection, storage, and processing of vast amounts of data. This book is designed as a comprehensive guide for anyone seeking to embark on a journey into data engineering or looking to deepen their understanding of its intricacies. Whether you are a seasoned data professional, a software engineer transitioning into data roles, or a student eager to explore the forefront of technological innovation, this book will equip you with the knowledge and skills necessary to navigate the complexities of modern data ecosystems. Each chapter is crafted to provide a blend of theoretical foundations, practical insights, and hands-on examples to help you on your way. So, let’s get started!
| Author | : Maxine Chen |
| Publisher | : |
| Total Pages | : 0 |
| Release | : 2024-03-02 |
| Genre | : Computers |
| ISBN | : |
Embark on a transformative journey into the realm of data science and big data analytics with 'Mastering Data Science and Big Data Analytics: Strategies and Tools for Effective Analysis.' This comprehensive guide unveils essential techniques, strategies, and tools necessary to navigate the vast landscape of big data with confidence and proficiency. From foundational concepts to advanced methodologies, this book provides a holistic understanding of data science principles, empowering both aspiring data scientists and seasoned professionals alike to harness the power of data to drive informed decision-making and innovation. Through clear explanations and real-world examples, discover how to leverage cutting-edge tools and technologies to extract actionable insights from complex datasets. With a focus on practical application, 'Mastering Data Science and Big Data Analytics' equips you with the skills to tackle real-world challenges head-on, whether it's uncovering hidden patterns, predicting future trends, or optimizing business processes. Explore the latest advancements in machine learning, artificial intelligence, and data visualization, and gain proficiency in popular programming languages and frameworks such as Python, R, TensorFlow, and Apache Spark. Whether you're a data enthusiast looking to expand your skill set or a business leader striving to unlock the full potential of your data assets, this book serves as an indispensable companion on the journey to mastering data science and big data analytics. Empower yourself to turn data into actionable insights and drive meaningful impact in an increasingly data-driven world.
| Author | : Prabhu TL |
| Publisher | : NestFame Creations Pvt Ltd. |
| Total Pages | : 285 |
| Release | : |
| Genre | : Computers |
| ISBN | : |
Big data is a term that describes the large volume of data – both structured and unstructured – that inundates a business on a day-to-day basis. But it’s not the amount of data that’s important. It’s what organizations do with the data that matters. Big data can be analyzed for insights that lead to better decisions and strategic business moves. The use of Big Data is becoming common these days by the companies to outperform their peers. In most industries, existing competitors and new entrants alike will use the strategies resulting from the analyzed data to compete, innovate and capture value. Big Data helps the organizations to create new growth opportunities and entirely new categories of companies that can combine and analyze industry data. These companies have ample information about the products and services, buyers and suppliers, consumer preferences that can be captured and analyzed. While the term “big data” is relatively new, the act of gathering and storing large amounts of information for eventual analysis is ages old. The concept gained momentum in the early 2000s when industry analyst Doug Laney articulated the now-mainstream definition of big data as the three Vs: Volume. Organizations collect data from a variety of sources, including business transactions, social media and information from sensor or machine-to-machine data. In the past, storing it would’ve been a problem – but new technologies (such as Hadoop) have eased the burden. The name 'Big Data' itself is related to a size which is enormous. Size of data plays very crucial role in determining value out of data. Also, whether a particular data can actually be considered as a Big Data or not, is dependent upon volume of data. Hence, 'Volume' is one characteristic which needs to be considered while dealing with 'Big Data'. Velocity. Data streams in at an unprecedented speed and must be dealt with in a timely manner. RFID tags, sensors and smart metering are driving the need to deal with torrents of data in near-real time. The term 'velocity' refers to the speed of generation of data. How fast the data is generated and processed to meet the demands, determines real potential in the data. Big Data Velocity deals with the speed at which data flows in from sources like business processes, application logs, networks and social media sites, sensors, Mobile devices, etc. The flow of data is massive and continuous. Variety. Data comes in all types of formats – from structured datasets numeric data in traditional databases to unstructured text documents, email, video, audio, stock ticker data and financial transactions. Variety refers to heterogeneous sources and the nature of data, both structured and unstructured. During earlier days, spreadsheets and databases were the only sources of data considered by most of the applications. Now days, data in the form of emails, photos, videos, monitoring devices, PDFs, audio, etc. is also being considered in the analysis applications. This variety of unstructured data poses certain issues for storage, mining and analysing data.
| Author | : Fabian Jaytox |
| Publisher | : Independently Published |
| Total Pages | : 0 |
| Release | : 2024-07-06 |
| Genre | : Computers |
| ISBN | : |
In the era of digital transformation, data is the new gold. Organizations worldwide are sitting on a treasure trove of information that, when properly harnessed, can lead to unprecedented business success and wealth. "Big Data Analytics: Converting Big Data to Big Wealth" is your comprehensive guide to unlocking the immense potential of big data and transforming it into substantial financial gains. Explore the Core Concepts The book starts with the basics, ensuring that readers of all backgrounds can grasp the fundamental principles of big data. You'll learn about the characteristics that define big data, including volume, velocity, variety, veracity, and value. Understand why big data is critical in today's business environment and how it differs from traditional data analysis. Dive into Advanced Tools and Technologies Navigate through the complex landscape of big data technologies with ease. This book offers an in-depth look at the essential tools and frameworks that make big data analytics possible. Discover the power of Hadoop and Spark for data processing, explore the capabilities of NoSQL databases, and learn how to utilize machine learning platforms for predictive analytics. Each technology is explained in detail, with practical examples and case studies to illustrate their real-world applications. Master Analytical Techniques "Big Data Analytics: Converting Big Data to Big Wealth" delves into the various analytical techniques that turn raw data into actionable insights. From data mining and pattern discovery to predictive analytics and machine learning, you will gain a thorough understanding of how to apply these methods to your data. Learn how to build predictive models, perform regression analysis, cluster data, and use decision trees to uncover hidden patterns and trends. Implement Effective Strategies Developing and implementing a robust big data analytics strategy is crucial for success. This book provides a step-by-step guide to creating a data-driven approach that aligns with your business goals. Learn best practices for data management, governance, and quality assurance. Understand the importance of building a cross-functional team and fostering a culture of continuous learning and innovation. Real-World Applications and Case Studies See how big data analytics is transforming industries across the globe. This book features a range of case studies and examples from sectors such as healthcare, finance, retail, manufacturing, and sports. Discover how companies use big data to enhance customer experiences, improve operational efficiency, drive innovation, and gain a competitive edge. Examples include fraud detection in financial transactions, personalized marketing in retail, predictive maintenance in manufacturing, and player performance analysis in sports. Overcome Challenges and Embrace Future Trends Every journey has its challenges, and big data analytics is no exception. Learn how to navigate common obstacles such as data quality issues, scalability, and security concerns. This book also looks ahead to the future of big data analytics, exploring emerging trends and technologies like AI integration, edge computing, and blockchain. Understand the ethical considerations and the importance of data privacy and security in the evolving landscape of big data. Who Should Read This Book? "Big Data Analytics: Converting Big Data to Big Wealth" is designed for a diverse audience. Business executives and managers will find strategic insights to drive their data initiatives. Data scientists and analysts will gain advanced techniques and methodologies. IT professionals and engineers will learn about the necessary infrastructure and technologies. Students and academics will appreciate the thorough exploration of theoretical and practical aspects of big data analytics.
