Products related to Data:
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Data Analytics in Marketing, Entrepreneurship, and Innovation
Innovation based in data analytics is a contemporary approach to developing empirically supported advances that encourage entrepreneurial activity inspired by novel marketing inferences.Data Analytics in Marketing, Entrepreneurship, and Innovation covers techniques, processes, models, tools, and practices for creating business opportunities through data analytics.It features case studies that provide realistic examples of applications.This multifaceted examination of data analytics looks at: Business analyticsApplying predictive analytics Using discrete choice analysis for decision-making Marketing and customer analyticsDeveloping new productsTechnopreneurshipDisruptive versus incremental innovationThe book gives researchers and practitioners insight into how data analytics is used in the areas of innovation, entrepreneurship, and marketing.Innovation analytics helps identify opportunities to develop new products and services, and improve existing methods of product manufacturing and service delivery.Entrepreneurial analytics facilitates the transformation of innovative ideas into strategy and helps entrepreneurs make critical decisions based on data-driven techniques.Marketing analytics is used in collecting, managing, assessing, and analyzing marketing data to predict trends, investigate customer preferences, and launch campaigns.
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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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Big Data Analytics
Big Data Analytics is intended for use as a textbook for third- and fourth-year students of B.E., B.Tech., B.Sc., BCA, MCA, and M.Tech. courses in IT, Software, and Computer Science Engineering.The book has been written to help students who enter the software industry to gain a broad understanding of Big Data and the nuances of handling it to extract useful information.Spread across 21 chapters, it elucidates the concept of Big Data and walks the reader through popular frameworks such as Hadoop, MongoDB, Pig and Hive that are used for processing Big Data.
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Social Data Analytics
This book is an introduction to social data analytics along with its challenges and opportunities in the age of Big Data and Artificial Intelligence.It focuses primarily on concepts, techniques and methods for organizing, curating, processing, analyzing, and visualizing big social data: from text to image and video analytics.It provides novel techniques in storytelling with social data to facilitate the knowledge and fact discovery.The book covers a large body of knowledge that will help practitioners and researchers in understanding the underlying concepts, problems, methods, tools and techniques involved in modern social data analytics.It also provides real-world applications of social data analytics, including: Sales and Marketing, Influence Maximization, Situational Awareness, customer success and Segmentation, and performance analysis of the industry.It provides a deep knowledge in social data analytics by comprehensively classifying the current state of research, by describing in-depth techniques and methods, and by highlighting future research directions.Lecturers will find a wealth of material to choose from for a variety of courses, ranging from undergraduate courses in data science to graduate courses in data analytics.
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Which data storage medium is suitable for long-term data storage?
For long-term data storage, optical discs such as Blu-ray discs and archival-grade DVDs are suitable options. These discs have a longer lifespan compared to traditional CDs and DVDs, and they are less susceptible to degradation from environmental factors. Additionally, solid-state drives (SSDs) with high-quality NAND flash memory can also be used for long-term data storage due to their durability and reliability. It is important to regularly check and migrate data to newer storage mediums to ensure long-term preservation.
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What is the difference between data and data storage devices?
Data refers to the information, facts, and figures that are stored and processed by computers. It can be in the form of text, images, videos, or any other digital content. On the other hand, data storage devices are physical devices that are used to store and retrieve data. These devices can include hard drives, solid-state drives, USB flash drives, memory cards, and optical discs. In summary, data is the information itself, while data storage devices are the physical means by which data is stored and accessed.
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How does a data storage work?
Data storage works by storing digital information in a physical or virtual medium, such as a hard drive, solid-state drive, or cloud storage. When data is stored, it is organized and indexed so that it can be easily accessed and retrieved when needed. The data is typically stored in binary code, represented by 0s and 1s, and can be written, read, and modified as necessary. Different storage mediums have different capacities and speeds, allowing for various types of data to be stored and accessed efficiently.
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What are two data storage devices?
Two data storage devices are hard disk drives (HDD) and solid-state drives (SSD). HDDs use spinning disks to store data and are commonly found in desktop computers and laptops. SSDs, on the other hand, use flash memory to store data and are known for their faster read and write speeds, making them popular in high-performance computers and servers. Both devices are used to store and retrieve digital information, but they differ in their technology and performance.
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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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Data Analytics : An Essential Beginner's Guide To Data Mining, Data Collection, Big Data Analytics For Business, And Business Intelligence Concepts
Say goodbye to scratching your head in confusionThis data analytics book could be the answer you're looking for...This book has lots of valuable eye-opening information about data analytics, which will help you understand the concept of data mining, data collection, big data analytics for business and business intelligence concepts.With this book, not only will you understand all the internal nitty-gritties about data analytics, you will also understand why data analytics is changing the business arena. You’ll realize that the high-performance analytics will enable you to do stuff that you never thought about before probably because the volumes of data were just too big (among other reasons) and so much more.We’ll begin by first examining what data analytics really means and what it entails. Do not fret when you meet challenging terms as you read on, as this book includes detailed explanations of words you may not understand.Here are just some of the topics that are discussed within this book:Overview Of Data Analytics: What Is Data Analytics (And Big Data Analytics)?,Data Analytics And Business Intelligence,Data Analysis And Data Analytics,Data Mining,Data Collection,Types Of Data Analytics,The Process: The Lifecycle Of Big Data Analytics,Behavioral Analytics: Using Big Data Analytics To Find Hidden Customer Behavior Patterns,Further Pattern Discovery In Advanced Analytics: Machine Learning,And Much, Much More,Get the book now and learn more about data analytics!
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Data Science and Analytics
Data Science and Analytics explores the solutions to problems in society, environment and in industry.With the increase in the availability of data, analytics has now become a major element in both the top line and the bottom line of any organization.This book explores perspectives on how big data and business analytics are increasingly essential in better decision making. This edited work explores the application of big data and business analytics by academics, researchers, industrial experts, policy makers and practitioners, helping the reader to understand how big data can be efficiently utilized in better managerial applications.Data Science and Analytics brings together researchers, engineers and practitioners to encompass a wide and diverse range of topics in a wide range of fields.The book will provide unique insights to researchers, academics and data scientists from a variety of disciplines interested in analyzing and application of big data analytics, as well as data analysts, students and scholars pursuing advanced study in big data.
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Data Science and Big Data Analytics : Discovering, Analyzing, Visualizing and Presenting Data
Data Science and Big Data Analytics is about harnessing the power of data for new insights.The book covers the breadth of activities and methods and tools that Data Scientists use.The content focuses on concepts, principles and practical applications that are applicable to any industry and technology environment, and the learning is supported and explained with examples that you can replicate using open-source software.This book will help you: Become a contributor on a data science teamDeploy a structured lifecycle approach to data analytics problemsApply appropriate analytic techniques and tools to analyzing big dataLearn how to tell a compelling story with data to drive business actionPrepare for EMC Proven Professional Data Science Certification Get started discovering, analyzing, visualizing, and presenting data in a meaningful way today!
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What are local data storage devices?
Local data storage devices are physical hardware devices that are used to store and retrieve digital data on a local level. These devices include hard disk drives (HDD), solid-state drives (SSD), USB flash drives, memory cards, and optical discs such as CDs and DVDs. Local data storage devices are used to store files, documents, photos, videos, and other digital content, and they provide a convenient and accessible way to store and access data without relying on an internet connection. These devices are commonly used in personal computers, laptops, and other electronic devices for storing and accessing data locally.
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Is data volume equivalent to storage space?
No, data volume is not equivalent to storage space. Data volume refers to the amount of data being generated, processed, or transmitted, while storage space refers to the capacity available to store that data. Data volume can vary based on the amount of information being produced or used, while storage space is a fixed amount that can be allocated to store data. It is possible to have a large data volume but limited storage space, or vice versa, depending on the specific needs and capabilities of a system.
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Can hackers access external data storage devices?
Yes, hackers can potentially access external data storage devices if they are able to gain unauthorized access to the device or the network it is connected to. This could be done through various means such as exploiting security vulnerabilities, using malware, or conducting phishing attacks to trick users into providing access. It is important for individuals and organizations to implement strong security measures such as encryption, access controls, and regular security updates to protect their external data storage devices from unauthorized access.
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How do you format data storage devices?
Data storage devices can be formatted using the built-in formatting tools provided by the operating system. This can typically be done by accessing the device through the Disk Management utility on Windows or the Disk Utility on macOS. When formatting a storage device, you can choose the file system (such as NTFS, exFAT, or HFS+) and allocation unit size. It's important to note that formatting a storage device will erase all data on it, so be sure to back up any important information before proceeding.
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