Products related to Data:
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Data and Analytics Strategy for Business : Unlock Data Assets and Increase Innovation with a Results-Driven Data Strategy
For many organizations data is a by-product, but for the smarter ones it is the heartbeat of their business.Most businesses have a wealth of data buried in their systems which, if used effectively, could increase revenue, reduce costs and risk and improve customer satisfaction and employee experience.Beginning with how to choose projects which reflect your organization's goals and how to make the business case for investing in data, this book then takes the reader through the five 'waves' of organizational data maturity.It takes the reader from getting started on the data journey with some quick wins, to how data can help your business become a leading innovator which systematically outperforms competitors. Data and Analytics Strategy for Business outlines how to build consistent, high-quality sources of data which will create business value and explores how automation, AI and machine learning can improve performance and decision making.Filled with real-world examples and case studies, this book is a stage-by-stage guide to designing and implementing a results-driven data strategy.
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Portfolio Management : Delivering on Strategy
Portfolio management is becoming the ‘must have’ for organizations to prosper and survive in this decade and beyond.No longer can the organizational focus be one of following best and repeatable practices as resource limitations mean only those programs, projects, and operational work that add business value can and should be pursued.Executives are focusing on strategic ability and managing complexity, which can only be done through a disciplined portfolio process in ensuring the best mix of programs, projects, and operational work is under way.In turn, the portfolio is constantly in flux as difficult decisions are made if a project, for example, is no longer contributing to business value and providing benefits and should be terminated to reallocate resources to one of higher priority.Commitment to this difficult approach is necessary at all levels, and communication is required so everyone knows how their work contributes to the organization’s strategic goals and objectives. Portfolio Management: Delivering on Strategy, Second Edition focuses on the benefits of portfolio management to the organization.Its goal is to provide senior executives a view on how portfolio management can deliver organizational strategy.The emphasis is on the specific aspects within the portfolio management discipline and how each aspect should be managed from a business perspective and not necessarily from a portfolio management perspective.Highlights of the book include:Agile portfolio management Delivering organizational value Portfolio management and uncertainty Portfolio governance Marketing a portfolio Portfolio management success Starting with a review of the project portfolio concept and its development, this book is a reference for executives and practitioners in the field, as well as a students and researchers studying portfolio management.
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Data Science and Data Analytics : Opportunities and Challenges
Data science is a multi-disciplinary field that uses scientific methods, processes, algorithms, and systems to extract knowledge and insights from structured (labeled) and unstructured (unlabeled) data.It is the future of Artificial Intelligence (AI) and a necessity of the future to make things easier and more productive.In simple terms, data science is the discovery of data or uncovering hidden patterns (such as complex behaviors, trends, and inferences) from data.Moreover, Big Data analytics/data analytics are the analysis mechanisms used in data science by data scientists.Several tools, such as Hadoop, R, etc., are used to analyze this large amount of data to predict valuable information and for decision-making.Note that structured data can be easily analyzed by efficient (available) business intelligence tools, while most of the data (80% of data by 2020) is in an unstructured form that requires advanced analytics tools.But while analyzing this data, we face several concerns, such as complexity, scalability, privacy leaks, and trust issues. Data science helps us to extract meaningful information or insights from unstructured or complex or large amounts of data (available or stored virtually in the cloud).Data Science and Data Analytics: Opportunities and Challenges covers all possible areas, applications with arising serious concerns, and challenges in this emerging field in detail with a comparative analysis/taxonomy. FEATURES Gives the concept of data science, tools, and algorithms that exist for many useful applications Provides many challenges and opportunities in data science and data analytics that help researchers to identify research gaps or problems Identifies many areas and uses of data science in the smart era Applies data science to agriculture, healthcare, graph mining, education, security, etc. Academicians, data scientists, and stockbrokers from industry/business will find this book useful for designing optimal strategies to enhance their firm’s productivity.
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Applied Fundamentals in Finance : Portfolio Management and Investments
This textbook provides a comprehensive introduction to portfolio management and investments.Focusing on four core areas – portfolio management, equities, bonds, and derivatives – it is primarily intended for undergraduate and graduate students alike.However, it will also benefit practitioners working in the fields of financial analysis and portfolio management and professionals who aspire to such professional activities in the financial industry.To ensure its high practical relevance, the book includes a host of case studies and examples from real-world practice, mainly from the German and Swiss financial markets.Additionally, the book shows how to implement the models in Microsoft Excel.
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How can one study data analysis and data management?
One can study data analysis and data management through a variety of methods. This can include enrolling in formal education programs such as a degree in data science, statistics, or computer science. Additionally, there are many online courses and tutorials available that cover data analysis and data management. Practical experience can also be gained through internships or working on real-world projects. It's important to continuously practice and apply the concepts learned through these methods to gain a deeper understanding of data analysis and data management.
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Does Amazon have my data and is there allegedly a data leak with returns or something similar?
Amazon does collect and store customer data as part of its business operations. There have been reports and allegations of data leaks related to Amazon's returns process, where customer information may have been exposed. However, Amazon has not confirmed any specific data leaks related to returns. It is always important to be cautious with personal information and to monitor for any potential data breaches or unauthorized access to your data.
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How does data management work in Final Cut Pro X?
In Final Cut Pro X, data management is primarily handled through the Library system. Users can create multiple Libraries to organize their media files, projects, and events. Within each Library, users can create Events to store media files and Projects to work on editing. Final Cut Pro X also allows users to consolidate media files within the Library to ensure all necessary files are stored in one place. Additionally, users can optimize and delete unused media to free up storage space within the Library.
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What is your question about portfolio management?
My question about portfolio management is how to effectively diversify a portfolio to minimize risk while maximizing returns. I am interested in understanding the different asset classes and investment strategies that can be used to achieve a well-balanced and diversified portfolio. Additionally, I would like to know how to monitor and rebalance a portfolio to ensure it remains aligned with my investment goals and risk tolerance.
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Modern Data Strategy
This book contains practical steps business users can take to implement data management in a number of ways, including data governance, data architecture, master data management, business intelligence, and others.It defines data strategy, and covers chapters that illustrate how to align a data strategy with the business strategy, a discussion on valuing data as an asset, the evolution of data management, and who should oversee a data strategy.This provides the user with a good understanding of what a data strategy is and its limits. Critical to a data strategy is the incorporation of one or more data management domains.Chapters on key data management domains—data governance, data architecture, master data management and analytics, offer the user a practical approach to data management execution within a data strategy.The intent is to enable the user to identify how execution on one or more data management domains can help solve business issues. This book is intended for business users who work with data, who need to manage one or more aspects of the organization’s data, and who want to foster an integrated approach for how enterprise data is managed.This book is also an excellent reference for students studying computer science and business management or simply for someone who has been tasked with starting or improving existing data management.
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Behavioral Finance and Your Portfolio : A Navigation Guide for Building Wealth
Become a more strategic and successful investor by identifying the biases impacting your decision making. In Behavioral Finance and Your Portfolio, acclaimed investment advisor and author Michael M.Pompian delivers an insightful and thorough guide to countering the negative effect of cognitive and behavioral biases on your financial decisions.You’ll learn about the “Big Five” behavioral biases and how they’re reducing your returns and leading to unwanted and unnecessary costs in your portfolio. Designed for investors who are serious about maximizing their gains, in this book you’ll discover how to: ?Take control of your decision-making—even when challenging markets push greed and fear to intolerable levels ?Reflect on how to make investment decisions using data-backed and substantiated information instead of emotion and bias ?Counter deep-seated biases like loss aversion, hindsight and overconfidence with self-awareness and hard facts ?Identify your personal investment psychology profile, which you can use to inform your future financial decision making Behavioral Finance and Your Portfolio was created for individual investors, but will also earn a place in the libraries of financial advisors, planners and portfolio managers who are determined to counteract the less principled and data-driven aspects of their decision making.
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Research Data Management and Data Literacies
Research Data Management and Data Literacies help researchers familiarize themselves with RDM, and with the services increasingly offered by libraries.This new volume looks at data-intensive science, or ‘Science 2.0’ as it is sometimes termed in commentary, from a number of perspectives, including the tasks academic libraries need to fulfil, new services that will come online in the near future, data literacy and its relation to other literacies, research support and the need to connect researchers across the academy, and other key issues, such as ‘data deluge,’ the importance of citations, metadata and data repositories. This book presents a solid resource that contextualizes RDM, including good theory and practice for researchers and professionals who find themselves tasked with managing research data.
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Python for Finance 2e : Mastering Data-Driven Finance
The financial industry has recently adopted Python at a tremendous rate, with some of the largest investment banks and hedge funds using it to build core trading and risk management systems.Updated for Python 3, the second edition of this hands-on book helps you get started with the language, guiding developers and quantitative analysts through Python libraries and tools for building financial applications and interactive financial analytics.Using practical examples throughout the book, author Yves Hilpisch also shows you how to develop a full-fledged framework for Monte Carlo simulation-based derivatives and risk analytics, based on a large, realistic case study.Much of the book uses interactive IPython Notebooks
Price: 63.99 £ | Shipping*: 0.00 £
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What opportunities does health management offer?
Health management offers opportunities to make a positive impact on people's lives by improving healthcare delivery and outcomes. It also provides opportunities for leadership and innovation in the healthcare industry, as well as the chance to work with diverse teams and stakeholders to address complex health challenges. Additionally, health management offers opportunities for career growth and advancement in a rapidly evolving and essential field.
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Do active mobile data consume data volume?
Yes, active mobile data does consume data volume. When your mobile data is turned on and you are using apps, browsing the internet, streaming videos, or downloading files, data is being consumed from your data plan. It is important to monitor your data usage to avoid exceeding your data limit and potentially incurring extra charges from your mobile service provider.
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Do activated mobile data consume data volume?
Yes, activated mobile data does consume data volume. When mobile data is turned on, it allows your device to connect to the internet using your cellular network, and any data used during this connection will be deducted from your data plan. Activities such as browsing the web, streaming videos, or using apps that require an internet connection will all consume data volume when mobile data is activated. It's important to monitor your data usage to avoid exceeding your plan's limits and incurring additional charges.
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What are master data and transactional data?
Master data refers to the core data entities of an organization, such as customer, product, employee, and supplier information. This data is typically static and does not change frequently. Master data is used as a reference point for transactional data. On the other hand, transactional data refers to the detailed records of day-to-day business activities, such as sales orders, purchase orders, invoices, and payments. This data is dynamic and changes frequently as business transactions occur. Transactional data is used to track and record the specific activities and events within an organization.
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