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Data Professionals at Work
by Malathi MahadevanEnjoy reading interviews with more than two dozen data professionals to see a picture of what it’s like to work in the industry managing and analyzing data, helping you to know what it takes to move from your current expertise into one of the fastest growing areas of technology today. Data is the hottest word of the century, and data professionals are in high demand. You may already be a data professional such as a database administrator or business intelligence analyst. Or you may be one of the many people who want to work as a data professional, and are curious how to get there. Either way, this collection helps you understand how data professionals work, what makes them successful, and what they do to keep up.You’ll find interviews in this book with database administrators, database programmers, data architects, business intelligence professionals, and analytics professionals. Interviewees work across industry sectors ranging from healthcare and banking to finance and transportation and beyond. Each chapter illuminates a successful professional at the top of their game, who shares what helped them get to the top, and what skills and attitudes combine to make them successful in their respective fields.Interviewees in the book include: Mindy Curnutt, Julie Smith, Kenneth Fisher, Andy Leonard, Jes Borland, Kevin Feasel, Ginger Grant, Vicky Harp, Kendra Little, Jason Brimhall, Tim Costello, Andy Mallon, Steph Locke, Jonathan Stewart, Joseph Sack, John Q. Martin, John Morehouse, Kathi Kellenberger, Argenis Fernandez, Kirsten Benzel, Tracy Boggiano, Dave Walden, Matt Gordon, Jimmy May, Drew Furgiuele, Marlon Ribunal, and Joseph Fleming. All of them have been successful in their careers, and share their perspectives on working and succeeding in the field as data and database professionals. What You'll LearnStand out as an outstanding professional in your area of data work by developing the right set of skills and attitudes that lead to successAvoid common mistakes and pitfalls, and recover from operational failures and bad technology decisionsUnderstand current trends and best practices, and stay out in front as the field evolvesBreak into working with data through database administration, business intelligence, or any of the other career paths represented in this bookManage stress and develop a healthy work-life balance no matter which career path you decide uponChoose a suitable path for yourself from among the different career paths in working with dataWho This Book Is ForDatabase administrators and developers, database and business intelligence architects, consultants, and analytic professionals, as well as those intent on moving into one of those career paths. Aspiring data professionals and those in related technical fields who want to make a move toward managing or analyzing data on a full-time basis will find the book useful. Existing data professionals who want to be outstanding and successful at what they do will also appreciate the book's advice and guidance.
Data Protection: Ensuring Data Availability
by Preston de GuiseThis is the fundamental truth about data protection: backup is dead. Or rather, backup and recovery, as a standalone topic, no longer has relevance in IT. As a standalone topic, it’s been killed off by seemingly exponential growth in storage and data, by the cloud, and by virtualization. So what is data protection? This book takes a holistic, business-based approach to data protection. It explains how data protection is a mix of proactive and reactive planning, technology and activities that allow for data continuity. It shows how truly effective data protection comes from a holistic approach considering the entire data lifecycle and all required SLAs. Data protection is neither RAID nor is it continuous availability, replication, snapshots or backups—it is all of them, combined in a considered and measured approach to suit the criticality of the data and meet all the requirements of the business. The book also discusses how businesses seeking to creatively leverage their IT investments and to drive through cost optimization are increasingly looking at data protection as a mechanism to achieve those goals. In addition to being a type of insurance policy, data protection is becoming an enabler for new processes around data movement and data processing. This book arms readers with information critical for making decisions on how data can be protected against loss in the cloud, on-premises, or in a mix of the two. It explains the changing face of recovery in a highly virtualized data center and techniques for dealing with big data. Moreover, it presents a model for where data recovery processes can be integrated with IT governance and management in order to achieve the right focus on recoverability across the business.
Data Protection: Ensuring Data Availability
by Preston de GuiseThe second edition of Data Protection goes beyond the traditional topics including deduplication, continuous availability, snapshots, replication, backup, and recovery, and explores such additional considerations as legal, privacy, and ethical issues. A new model is presented for understanding and planning the various aspects of data protection, which is essential to developing holistic strategies. The second edition also addresses the cloud and the growing adoption of software and function as a service, as well as effectively planning over the lifespan of a workload: what the best mix of traditional and cloud native data protection services might be. Virtualization continues to present new challenges to data protection, and the impact of containerization is examined. The book takes a holistic, business-based approach to data protection. It explains how data protection is a mix of proactive and reactive planning, technology, and activities that allow for data continuity. There are three essential activities that refer to themselves as data protection; while they all overlap in terms of scope and function, each operates as a reasonably self-contained field with its own specialists and domain nomenclature. These three activities are: • Data protection as a storage and recovery activity • Data protection as a security activity • Data protection as a privacy activity These activities are covered in detail, with a focus on how organizations can use them to leverage their IT investments and optimize costs. The book also explains how data protection is becoming an enabler for new processes around data movement and data processing. This book arms readers with information critical for making decisions on how data can be protected against loss in the cloud, on premises, or in a mix of the two. It explains the changing face of recovery in a highly virtualized datacenter and techniques for dealing with big data. Moreover, it presents a model for where data recovery processes can be integrated with IT governance and management in order to achieve the right focus on recoverability across the business. About the Author Preston de Guise has been working with data recovery products for his entire career—designing, implementing, and supporting solutions for governments, universities, and businesses ranging from SMEs to Fortune 500 companies. This broad exposure to industry verticals and business sizes has enabled Preston to understand not only the technical requirements of data protection and recovery, but the management and procedural aspects too.
Data Protection: The Wake of AI and Machine Learning
by Chaminda Hewage Lasith Yasakethu Dushmantha Nalin K. JayakodyThis book provides a thorough and unique overview of the challenges, opportunities and solutions related with data protection in the age of AI and ML technologies. It investigates the interface of data protection and new technologies, emphasising the growing need to safeguard personal and confidential data from unauthorised access and change. The authors emphasize the crucial need of strong data protection regulations, focusing on the consequences of AI and ML breakthroughs for privacy and individual rights. This book emphasizes the multifarious aspect of data protection, which goes beyond technological solutions to include ethical, legislative and societal factors. This book explores into the complexity of data protection in the age of AI and ML. It investigates how massive volumes of personal and sensitive data are utilized to train and develop AI models, demanding novel privacy-preserving strategies such as anonymization, differential privacy and federated learning. The duties and responsibilities of engineers, policy makers and ethicists in minimizing algorithmic bias and ensuring ethical AI use are carefully defined. Key developments, such as the influence of the European Union's General Data Protection Regulation (GDPR) and the EU AI Act on data protection procedures, are reviewed critically. This investigation focusses not only on the tactics used, but also on the problems and successes in creating a secure and ethical AI ecosystem. This book provides a comprehensive overview of the efforts to integrate data protection into AI innovation, including valuable perspectives on the effectiveness of these measures and the ongoing adjustments required to address the fluid nature of privacy concerns. This book is a helpful resource for upper-undergraduate and graduate computer science students, as well as others interested in cybersecurity and data protection. Researchers in AI, ML, and data privacy as well as data protection officers, politicians, lawmakers and decision-makers will find this book useful as a reference.
Data Protection: Governance, Risk Management, and Compliance
by David G. HillFailure to appreciate the full dimensions of data protection can lead to poor data protection management, costly resource allocation issues, and exposure to unnecessary risks. Data Protection: Governance, Risk Management, and Compliance explains how to gain a handle on the vital aspects of data protection.The author begins by building the foundatio
Data Protection and Privacy: (Law, Governance and Technology Series #36)
by Paul De Hert Serge Gutwirth Ronald Leenes Rosamunde Van BrakelThis book features peer reviewed contributions from across the disciplines on themes relating to protection of data and to privacy protection. The authors explore fundamental and legal questions, investigate case studies and consider concepts and tools such as privacy by design, the risks of surveillance and fostering trust. Readers may trace both technological and legal evolution as chapters examine current developments in ICT such as cloud computing and the Internet of Things. Written during the process of the fundamental revision of revision of EU data protection law (the 1995 Data Protection Directive), this volume is highly topical. Since the European Parliament has adopted the General Data Protection Regulation (Regulation 2016/679), which will apply from 25 May 2018, there are many details to be sorted out. This volume identifies and exemplifies key, contemporary issues. From fundamental rights and offline alternatives, through transparency requirements to health data breaches, the reader is provided with a rich and detailed picture, including some daring approaches to privacy and data protection. The book will inform and inspire all stakeholders. Researchers with an interest in the philosophy of law and philosophy of technology, in computers and society, and in European and International law will all find something of value in this stimulating and engaging work.
Data Protection and Privacy in Healthcare: Research and Innovations
by Ahmed Elngar, Ambika Pawar, and Prathamesh ChuriThe Healthcare industry is one of the largest and rapidly developing industries. Over the last few years, healthcare management is changing from disease centered to patient centered. While on one side the analysis of healthcare data plays an important role in healthcare management, but on the other side the privacy of a patient’s record must be of equal concern. This book uses a research-oriented approach and focuses on privacy-based healthcare tools and technologies. It offers details on privacy laws with real-life case studies and examples, and addresses privacy issues in newer technologies such as Cloud, Big Data, and IoT. It discusses the e-health system and preserving its privacy, and the use of wearable technologies for patient monitoring, data streaming and sharing, and use of data analysis to provide various health services. This book is written for research scholars, academicians working in healthcare and data privacy domains, as well as researchers involved with healthcare law, and those working at facilities in security and privacy domains. Students and industry professionals, as well as medical practitioners might also find this book of interest.
Data Protection Compliance in the UK
by Rosemary Jay Jenna ClarkeOrganisations now face much stiffer penalties for breaching the Data Protection Act, which makes this pocket guide more valuable than ever!Your company holds personal information about your customers in electronic form. Almost certainly, you will also keep records on your staff in your computer system. In the digital age, managing personal information has become a key organisational challenge. For legal reasons, everyone has to understand the proper way to handle this personal data. ComplianceYour business needs to operate in compliance with the Data Protection Act. This means your company has to take the right steps towards secure management of personal digital information. Under the Data Protection Act, some faults are treated as criminal offences. Where failure to comply is the fault of a manager, the manager can be prosecuted along with the company. A tougher regulatory environmentKnowingly, or recklessly, obtaining or disclosing personal data is an offence under Section 55 of the Data Protection Act. In 2009, the Coroners and Justice Act amended the DPA to give the Information Commissioner the power to carry out compulsory assessments of government departments. This year, the government has further tightened the enforcement regime for the DPA. On 6 April 2010, tougher penalties came into effect, including custodial sentences for deliberate or careless disclosure of personal data. Deliberate, or reckless, disclosure of personal data by your staff will also put you in the firing line as their employer. The Information Commissioner''s Office has acquired new powers to fine companies up to £500,000 for serious contraventions of the Data Protection Act. This pocket guide gives you a clear description of the Data Protection Act, outlining its terms and explaining its requirements. It is essential reading if you have a responsibility for the security of personal data, especially if you are a director, a manager or an IT professional. The pocket guide includes handy good practice tips for staff. The easy-to-follow checklist tells you the practical steps you should be taking in order to comply with the Data Protection Act. Benefits to business include: * Avoid expensive litigation Failure to comply with the Data Protection Act can lead to a heavy fine, as well as complaints and reputational damage. Use this book to help your company avoid embarrassing disputes and costly litigation. * Avoid illegal monitoring and interception There are good reasons why you might want to listen to customer calls (monitoring) or to record them (interception). Use this book to ensure that you monitor and intercept calls and e-mails in a way that is legal. * Understand transfer of data overseas To improve customer service or streamline operations, your company may wish to transfer personal digital information overseas (offshoring). This book advises you on when it is legal to do this. It offers you guidance on transfer of data outside the European Economic Area, and on the US-EU Safe Harbor Agreement. * Handle electronic marketing properly You need to understand the special rules that concern e-mail marketing. Use this book to make sure that your online marketing campaigns are being run in a way that is legal. Data Protection Compliance in the UK has been published as an inexpensive and easily read introduction for any employee required to support compliance with the DPA. It: * Outlines UK and EU data protection regulations; * Describes the rights of individuals; * Explains the security obligations of organizations; * Addresses topics including o IT monitoring and interception, o enforcement provisions and o penalties for non-compliance. Reputational risksA survey conducted by IT Governance has shown that only around half of those employees who handle personal information have been trained in their Data Protection Act responsibilities. And yet failure to comply with the Data Protection Act can have damaging consequences. The scandal at T-Mobile has highlighted the need for businesses to tighten up their data securi...
Data Protection for Photographers
by Patrick H. CorriganAll photographers, both amateur and professional, are faced with the important issues of data protection and storage. Without knowledge of the options, tools, and procedures for safe and effective image protection and storage, photographers run the serious risk of losing their image files. This book offers critical information about the best hardware, software, procedures, and practices for capturing, storing, and preserving images and other data. This book explains current data protection and storage technologies in everyday terms. It describes effective procedures for protecting data, from capture to backup and archiving. Descriptions of specific products applicable to Windows, MacOS, and Linux systems are provided.
Data Protection in a Post-Pandemic Society: Laws, Regulations, Best Practices and Recent Solutions
by Chaminda Hewage Yogachandran Rahulamathavan Deepthi RatnayakeThis book offers the latest research results and predictions in data protection with a special focus on post-pandemic society. This book also includes various case studies and applications on data protection. It includes the Internet of Things (IoT), smart cities, federated learning, Metaverse, cryptography and cybersecurity. Data protection has burst onto the computer security scene due to the increased interest in securing personal data. Data protection is a key aspect of information security where personal and business data need to be protected from unauthorized access and modification. The stolen personal information has been used for many purposes such as ransom, bullying and identity theft. Due to the wider usage of the Internet and social media applications, people make themselves vulnerable by sharing personal data. This book discusses the challenges associated with personal data protection prior, during and post COVID-19 pandemic. Some of these challenges are caused by the technological advancements (e.g. Artificial Intelligence (AI)/Machine Learning (ML) and ChatGPT). In order to preserve the privacy of the data involved, there are novel techniques such as zero knowledge proof, fully homomorphic encryption, multi-party computations are being deployed. The tension between data privacy and data utility drive innovation in this area where numerous start-ups around the world have started receiving funding from government agencies and venture capitalists. This fuels the adoption of privacy-preserving data computation techniques in real application and the field is rapidly evolving. Researchers and students studying/working in data protection and related security fields will find this book useful as a reference.
Data Protection in the Internet (Ius Comparatum - Global Studies in Comparative Law #38)
by Dário Moura Vicente Sofia de Vasconcelos CasimiroThis book identifies and explains the different national approaches to data protection – the legal regulation of the collection, storage, transmission and use of information concerning identified or identifiable individuals – and determines the extent to which they could be harmonised in the foreseeable future. In recent years, data protection has become a major concern in many countries, as well as at supranational and international levels. In fact, the emergence of computing technologies that allow lower-cost processing of increasing amounts of information, associated with the advent and exponential use of the Internet and other communication networks and the widespread liberalization of the trans-border flow of information have enabled the large-scale collection and processing of personal data, not only for scientific or commercial uses, but also for political uses. A growing number of governmental and private organizations now possess and use data processing in order to determine, predict and influence individual behavior in all fields of human activity. This inevitably entails new risks, from the perspective of individual privacy, but also other fundamental rights, such as the right not to be discriminated against, fair competition between commercial enterprises and the proper functioning of democratic institutions. These phenomena have not been ignored from a legal point of view: at the national, supranational and international levels, an increasing number of regulatory instruments – including the European Union’s General Data Protection Regulation applicable as of 25 May 2018 – have been adopted with the purpose of preventing personal data misuse. Nevertheless, distinct national approaches still prevail in this domain, notably those that separate the comprehensive and detailed protective rules adopted in Europe since the 1995 Directive on the processing of personal data from the more fragmented and liberal attitude of American courts and legislators in this respect. In a globalized world, in which personal data can instantly circulate and be used simultaneously in communications networks that are ubiquitous by nature, these different national and regional approaches are a major source of legal conflict.
Data Protection Law: A Comparative Analysis of Asia-Pacific and European Approaches
by Robert Walters Leon Trakman Bruno ZellerThis book provides a comparison and practical guide for academics, students, and the business community of the current data protection laws in selected Asia Pacific countries (Australia, India, Indonesia, Japan Malaysia, Singapore, Thailand) and the European Union.The book shows how over the past three decades the range of economic, political, and social activities that have moved to the internet has increased significantly. This technological transformation has resulted in the collection of personal data, its use and storage across international boundaries at a rate that governments have been unable to keep pace. The book highlights challenges and potential solutions related to data protection issues arising from cross-border problems in which personal data is being considered as intellectual property, within transnational contracts and in anti-trust law. The book also discusses the emerging challenges in protecting personal data and promoting cyber security. The book provides a deeper understanding of the legal risks and frameworks associated with data protection law for local, regional and global academics, students, businesses, industries, legal profession and individuals.
The Data Protection Officer: Profession, Rules, and Role
by Paul LambertThe EU's General Data Protection Regulation created the position of corporate Data Protection Officer (DPO), who is empowered to ensure the organization is compliant with all aspects of the new data protection regime. Organizations must now appoint and designate a DPO. The specific definitions and building blocks of the data protection regime are enhanced by the new General Data Protection Regulation and therefore the DPO will be very active in passing the message and requirements of the new data protection regime throughout the organization. This book explains the roles and responsiblies of the DPO, as well as highlights the potential cost of getting data protection wrong.
Data Protection on the Move: Current Developments in ICT and Privacy/Data Protection (Law, Governance and Technology Series #24)
by Serge Gutwirth Ronald Leenes Paul HertThis volume brings together papers that offer methodologies, conceptual analyses, highlight issues, propose solutions, and discuss practices regarding privacy and data protection. It is one of the results of the eight annual International Conference on Computers, Privacy, and Data Protection, CPDP 2015, held in Brussels in January 2015. The book explores core concepts, rights and values in (upcoming) data protection regulation and their (in)adequacy in view of developments such as Big and Open Data, including the right to be forgotten, metadata, and anonymity. It discusses privacy promoting methods and tools such as a formal systems modeling methodology, privacy by design in various forms (robotics, anonymous payment), the opportunities and burdens of privacy self management, the differentiating role privacy can play in innovation. The book also discusses EU policies with respect to Big and Open Data and provides advice to policy makers regarding these topics. Also attention is being paid to regulation and its effects, for instance in case of the so-called 'EU-cookie law' and groundbreaking cases, such as Europe v. Facebook. This interdisciplinary book was written during what may turn out to be the final stages of the process of the fundamental revision of the current EU data protection law by the Data Protection Package proposed by the European Commission. It discusses open issues and daring and prospective approaches. It will serve as an insightful resource for readers with an interest in privacy and data protection.
Data Push Apps with HTML5 SSE
by Darren CookMake sure your website or web application users get content updates right now with minimal latency. This concise guide shows you how to push new data from the server to clients with HTML5 Server-Sent Events (SSE), an exceptional technology that doesn't require constant polling or user interaction. You'll learn how to build a real-world SSE application from start to finish that solves a demanding domain problem.You'll also discover how to increase that application's desktop and mobile browser support from 60% to 99%, using different fallback solutions. If you're familiar with HTML, HTTP, and basic JavaScript, you're ready to get started.Determine whether SSE, WebSockets, or data pull is best for your organizationDevelop a working SSE application complete with backend and frontend solutionsAddress error handling, system recovery, and other issues to make the application production-qualityExplore two fallback solutions for browsers that don't support SSETackle security issues, including authorization and "disallowed origin"Develop realistic, repeatable data that's useful in test-driven SSE designLearn SSE protocol elements not covered in the example application
Data Quality: Empowering Businesses with Analytics and AI
by Prashanth SouthekalDiscover 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 businessAn 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.
Data Quality and Trust in Big Data: 5th International Workshop, QUAT 2018, Held in Conjunction with WISE 2018, Dubai, UAE, November 12–15, 2018, Revised Selected Papers (Lecture Notes in Computer Science #11235)
by Hakim Hacid Quan Z. Sheng Tetsuya Yoshida Azadeh Sarkheyli Rui ZhouThis book constitutes revised selected papers from the International Workshop on Data Quality and Trust in Big Data, QUAT 2018, which was held in conjunction with the International Conference on Web Information Systems Engineering, WISE 2018, in Dubai, UAE, in November 2018. The 9 papers presented in this volume were carefully reviewed and selected from 15 submissions. They deal with novel ideas and solutions related to the problems of exploring, assessing, monitoring, improving, and maintaining the quality of data and trust for Big Data.
Data Quality Engineering in Financial Services: Applying Manufacturing Techniques To Data
by Brian BuzzelliData quality will either make you or break you in the financial services industry. Missing prices, wrong market values, trading violations, client performance restatements, and incorrect regulatory filings can all lead to harsh penalties, lost clients, and financial disaster. This practical guide provides data analysts, data scientists, and data practitioners in financial services firms with the framework to apply manufacturing principles to financial data management, understand data dimensions, and engineer precise data quality tolerances at the datum level and integrate them into your data processing pipelines.You'll get invaluable advice on how to:Evaluate data dimensions and how they apply to different data types and use casesDetermine data quality tolerances for your data quality specificationChoose the points along the data processing pipeline where data quality should be assessed and measuredApply tailored data governance frameworks within a business or technical function or across an organizationPrecisely align data with applications and data processing pipelinesAnd more
Data Quality Fundamentals
by Barr Moses Lior Gavish Molly VorwerckDo your product dashboards look funky? Are your quarterly reports stale? Is the data set you're using broken or just plain wrong? These problems affect almost every team, yet they're usually addressed on an ad hoc basis and in a reactive manner. If you answered yes to these questions, this book is for you. Many data engineering teams today face the "good pipelines, bad data" problem. It doesn't matter how advanced your data infrastructure is if the data you're piping is bad. In this book, Barr Moses, Lior Gavish, and Molly Vorwerck, from the data observability company Monte Carlo, explain how to tackle data quality and trust at scale by leveraging best practices and technologies used by some of the world's most innovative companies. Build more trustworthy and reliable data pipelinesWrite scripts to make data checks and identify broken pipelines with data observabilityLearn how to set and maintain data SLAs, SLIs, and SLOsDevelop and lead data quality initiatives at your companyLearn how to treat data services and systems with the diligence of production softwareAutomate data lineage graphs across your data ecosystemBuild anomaly detectors for your critical data assets
Data Quality in the Age of AI: Building a foundation for AI strategy and data culture
by Andrew JonesUnlock the power of data with expert insights to enhance data quality, maximizing the potential of AI, and establishing a data-centric cultureKey FeaturesGain a profound understanding of the interplay between data quality and AIExplore strategies to improve data quality with practical implementation and real-world resultsAcquire the skills to measure and evaluate data quality, empowering data-driven decisionsPurchase of the Kindle book includes a free PDF eBookBook 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 learnDiscover actionable steps to establish data quality as the foundation of your data cultureEnhance data quality directly at its source with effective strategies and best practicesElevate data quality standards and enhance data literacy within your organizationIdentify and measure data quality within the datasetAdopt a product mindset to address data quality challengesExplore emerging architectural patterns like data mesh and data contractsAssign roles, responsibilities, and incentives for data generatorsGain insights from real-world case studiesWho this book is forThis 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.
Data Quality Management in the Data Age: Excellence in Data Quality for Enhanced Digital Economic Growth (SpringerBriefs in Service Science)
by Haiyan YuThis book addresses data quality management for data markets, including foundational quality issues in modern data science. By clarifying the concept of data quality, its impact on real-world applications, and the challenges stemming from poor data quality, it will equip data scientists and engineers with advanced skills in data quality management, with a particular focus on applications within data markets. This will help them create an environment that encourages potential data sellers with high-quality data to join the market, ultimately leading to an improvement in overall data quality. High-quality data, as a novel factor of production, has assumed a pivotal role in driving digital economic development. The acquisition of such data is particularly important for contemporary decision-making models. Data markets facilitate the procurement of high-quality data and thereby enhance the data supply. Consequently, potential data sellers with high-quality data are incentivized to enter the market, an aspect that is particularly relevant in data-scarce domains such as personalized medicine and services. Data scientists have a pivotal role to play in both the intellectual vitality and the practical utility of high-quality data. Moreover, data quality control presents opportunities for data scientists to engage with less structured or ambiguous problems. The book will foster fruitful discussions on the contributions that various scientists and engineers can make to data quality and the further evolution of data markets.
Data Rules: Reinventing the Market Economy (Acting with Technology)
by Jannis Kallinikos Cristina AlaimoA new social science framework for studying the unprecedented social and economic restructuring driven by digital data.Digital data have become the critical frontier where emerging economic practices and organizational forms confront the traditional economic order and its institutions. In Data Rules, Cristina Alaimo and Jannis Kallinikos establish a social science framework for analyzing the unprecedented social and economic restructuring brought about by data. Working at the intersection of information systems and organizational studies, they draw extensively on intellectual currents in sociology, semiotics, cognitive science and technology, and social theory. Making the case for turning &“data-making&” into an area of inquiry of its own, the authors uncover how data are deeply implicated in rewiring the institutions of the market economy.The authors associate digital data with the decentering of organizations. As they point out, centered systems make sense only when firms (and formal organizations more broadly) can keep the external world at arm&’s length and maintain a relative operation independence from it. These patterns no longer hold. Data transform the production of goods and services to an endless series of exchanges and interactions that defeat the functional logics of markets and organizations. The diffusion of platforms and ecosystems is indicative of these broader transformations. Rather than viewing data as simply a force of surveillance and control, the authors place the transformative potential of data at the center of an emerging socioeconomic order that restructures society and its institutions.
Data Science: Best Practices mit Python
by Benjamin M. Abdel-KarimDieses Buch entstand aus der Motivation heraus, eines der ersten deutschsprachigen Nachschlagewerke zu entwickeln, in welchem relativ simple Quellcode-Beispiele enthalten sind, um so Lösungsansätze für die (wiederkehrenden) Programmierprobleme in der Datenanalyse weiterzugeben. Dabei ist dieses Werk nicht uneigennützig verfasst worden. Es enthält Lösungswege für immer wiederkehrende Problemstellungen die ich über meinen täglichen Umgang entwickelt habe Zweifellos gehört das Nachschlagen von Lösungsansätzen in Büchern oder im Internet zur normalen Arbeit eines Programmierers. Allerdings ist diese Suche in der Regel ein unstrukturierter und damit, zumindest teilweise, ein zeitaufwendiger Prozess.Unabhängig davon, ob Sie das Buch als Student, Mitarbeiter oder Gründer lesen, hoffe ich, dass Ihnen dieses Nachschlagewerk ein wertvoller Helfer für die ersten Anfänge sein wird. Ich gehe davon aus, dass jede Person die Grundlagen der Datenanalyse mit Hilfe moderner Programmiersprachen erlernen kann.
Data Science: 5th International Conference of Pioneering Computer Scientists, Engineers and Educators, ICPCSEE 2019, Guilin, China, September 20–23, 2019, Proceedings, Part I (Communications in Computer and Information Science #1058)
by Xiaohui Cheng Weipeng Jing Xianhua Song Zeguang LuThis two volume set (CCIS 1058 and 1059) constitutes the refereed proceedings of the 5th International Conference of Pioneering Computer Scientists, Engineers and Educators, ICPCSEE 2019 held in Guilin, China, in September 2019. The 104 revised full papers presented in these two volumes were carefully reviewed and selected from 395 submissions. The papers cover a wide range of topics related to basic theory and techniques for data science including data mining; data base; net work; security; machine learning; bioinformatics; natural language processing; software engineering; graphic images; system; education; application.
Data Science: Konzepte, Erfahrungen, Fallstudien und Praxis
by Detlev Frick Andreas Gadatsch Jens Kaufmann Birgit Lankes Christoph Quix Andreas Schmidt Uwe SchmitzData Science ist in vielen Organisationen angekommen und oft alltägliche Praxis. Dennoch stehen viele Verantwortliche vor der Herausforderung, sich erstmalig mit konkreten Fragestellungen zu beschäftigen oder laufende Projekte weiterzuentwickeln. Die Spannbreite der Methoden, Werkzeuge und Anwendungsmöglichkeiten ist sehr groß und entwickelt sich kontinuierlich weiter. Die Vielzahl an Publikationen zu Data Science ist spezialisiert und behandelt fokussiert Einzelaspekte. Das vorliegende Werk gibt den Leserinnen und Lesern eine umfassende Orientierung zum Status Quo aus der wissenschaftlichen Perspektive und zahlreiche vertiefende Darstellungen praxisrelevanter Aspekte. Die Inhalte bauen auf den wissenschaftlichen CAS-Zertifikatskursen zu Big Data und Data Science der Hochschule Niederrhein in Kooperation mit der Hochschule Bonn-Rhein-Sieg und der FH Dortmund auf. Sie berücksichtigen wissenschaftliche Grundlagen und Vertiefungen, aber auch konkrete Erfahrungen aus Data Science Projekten. Das Buch greift praxisrelevante Fragen auf wissenschaftlichem Niveau aus Sicht der Rollen eines „Data Strategist“, „Data Architect“ und „Data Analyst“ auf und bindet erprobte Praxiserfahrungen u. a. von Seminarteilnehmern mit ein. Das Buch gibt für Interessierte einen Einblick in die aktuell relevante Vielfalt der Aspekte zu Data Science bzw. Big Data und liefert Hinweise für die praxisnahe Umsetzung.