Products related to Analytics:
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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 Analytics Initiatives : Managing Analytics for Success
The categorisation of analytical projects could help to simplify complexity reasonably and, at the same time, clarify the critical aspects of analytical initiatives.But how can this complex work be categorized? What makes it so complex?Data Analytics Initiatives: Managing Analytics for Success emphasizes that each analytics project is different.At the same time, analytics projects have many common aspects, and these features make them unique compared to other projects.Describing these commonalities helps to develop a conceptual understanding of analytical work.However, features specific to each initiative affects the entire analytics project lifecycle.Neglecting them by trying to use general approaches without tailoring them to each project can lead to failure. In addition to examining typical characteristics of the analytics project and how to categorise them, the book looks at specific types of projects, provides a high-level assessment of their characteristics from a risk perspective, and comments on the most common problems or challenges.The book also presents examples of questions that could be asked of relevant people to analyse an analytics project.These questions help to position properly the project and to find commonalities and general project challenges.
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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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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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Are Instagram analytics apps legal?
Yes, Instagram analytics apps are legal as long as they comply with Instagram's terms of service and data privacy regulations. These apps provide users with insights and data about their Instagram account performance, such as follower growth, engagement metrics, and audience demographics. It is important to choose a reputable analytics app that prioritizes user privacy and data security to ensure compliance with legal requirements.
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Where can one study Biomedical Analytics?
One can study Biomedical Analytics at various universities and colleges that offer programs in health informatics, bioinformatics, or biomedical data science. Some well-known institutions that offer programs in Biomedical Analytics include Stanford University, Harvard University, Johns Hopkins University, and the University of California, Los Angeles. Additionally, there are online programs and professional certifications available for those looking to specialize in Biomedical Analytics.
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How can I access external YouTube analytics?
To access external YouTube analytics, you can use YouTube's Analytics API. This API allows you to retrieve data and metrics from your YouTube channel and videos programmatically. You will need to set up a project in the Google Developers Console, obtain API credentials, and then use these credentials to make requests to the Analytics API. This will allow you to access detailed analytics data such as views, watch time, and audience demographics for your YouTube content.
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What is the question for evaluation in Google Analytics?
The question for evaluation in Google Analytics is typically focused on understanding user behavior and website performance. It could be something like "What are the top pages on my website in terms of traffic and engagement?" or "How are users finding my website and what are the most effective acquisition channels?" These questions help businesses and website owners to analyze and optimize their online presence for better performance and user experience.
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Augmented Analytics : Enabling Analytics Transformation for Data-Informed Decisions
Augmented Analytics isn't just another book on data and analytics; it's a holistic resource for reimagining how your entire organization interacts with information so that it becomes insight-driven. Go beyond traditional, limited ways of making sense of data.Augmented Analytics provides a dynamic, actionable strategy for improving your organization's analytical capabilities.With this book, you can infuse your workflows with intelligent automation and modern artificial intelligence, empowering more team members to make informed, data-driven decisions. Be aware: This book is not just about adding another forecast to your dashboard.It goes deeper, presenting a holistic approach to fostering a data-driven culture of analytics excellence throughout your organization. You'll explore:Key elements and building blocks of augmented analytics, including its benefits, potential challenges, and relevance in today's business landscapeBest practices for preparing and implementing augmented analytics in your organization, including analytics roles, mindset, toolset, and skill setBest practices for data enablement, liberalization, trust, and accessibilityHow to apply a use case approach to drive business value and use augmented analytics as an enabler, with selected case studiesDrawing on extensive, real-world experience leading large organizations through this transformation, the authors provide a clear, actionable path to accelerate your organization's journey to analytical excellence.
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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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Advances in Subsurface Data Analytics
Advances in Subsurface Data Analytics: Traditional and Physics-Based Approaches brings together the fundamentals of popular and emerging machine learning (ML) algorithms with their applications in subsurface analysis, including geology, geophysics, petrophysics, and reservoir engineering.The book is divided into four parts: traditional ML, deep learning, physics-based ML, and new directions, with an increasing level of diversity and complexity of topics.Each chapter focuses on one ML algorithm with a detailed workflow for a specific application in geosciences.Some chapters also compare the results from an algorithm with others to better equip the readers with different strategies to implement automated workflows for subsurface analysis. Advances in Subsurface Data Analytics: Traditional and Physics-Based Approaches will help researchers in academia and professional geoscientists working on the subsurface-related problems (oil and gas, geothermal, carbon sequestration, and seismology) at different scales to understand and appreciate current trends in ML approaches, their applications, advances and limitations, and future potential in geosciences by bringing together several contributions in a single volume.
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Data Analytics for Internal Auditors
There are many webinars and training courses on Data Analytics for Internal Auditors, but no handbook written from the practitioner’s viewpoint covering not only the need and the theory, but a practical hands-on approach to conducting Data Analytics.The spread of IT systems makes it necessary that auditors as well as management have the ability to examine high volumes of data and transactions to determine patterns and trends.The increasing need to continuously monitor and audit IT systems has created an imperative for the effective use of appropriate data mining tools.This book takes an auditor from a zero base to an ability to professionally analyze corporate data seeking anomalies.
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Can someone explain to me what Google Analytics is?
Google Analytics is a web analytics service offered by Google that allows website owners to track and analyze their website traffic. It provides valuable insights into how users interact with a website, including information about the number of visitors, their demographics, the pages they visit, and how they found the website. This data can help website owners make informed decisions about their marketing strategies, content, and user experience to improve their website's performance. Overall, Google Analytics is a powerful tool for understanding and optimizing website traffic.
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How can the Google Analytics cookie be a first-party cookie?
The Google Analytics cookie can be a first-party cookie because it is set by the website domain that the user is visiting. When a user visits a website that uses Google Analytics, the website sets the Google Analytics cookie on the user's browser. This means that the cookie is considered a first-party cookie because it is set by the same domain that the user is interacting with. As a result, the cookie can be used to track and analyze user behavior on that specific website.
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Which offers better opportunities in the job market: developing a data analytics app or web development?
Both developing a data analytics app and web development offer great opportunities in the job market, but the demand for data analytics skills is currently higher. Data analytics is a rapidly growing field, and businesses are increasingly relying on data to make informed decisions. Developing a data analytics app requires skills in data analysis, programming, and understanding of business needs, making it a valuable skill set in the job market. However, web development also offers great opportunities, especially with the increasing demand for online presence and e-commerce. Ultimately, both fields offer promising career prospects, but data analytics may currently have a slight edge in the job market.
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How can one use plausible analytics with a web app on a server?
Plausible analytics can be used with a web app on a server by integrating the Plausible tracking code into the web app's codebase. This tracking code will then collect data on user interactions and behavior on the web app. The data collected can be analyzed to gain insights into user engagement, popular features, and areas for improvement. By using Plausible analytics, developers can make data-driven decisions to optimize the web app for better user experience and performance.
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