Unstructured Content
DOWNLOAD
Download Unstructured Content PDF/ePub or read online books in Mobi eBooks. Click Download or Read Online button to get Unstructured Content book now. This website allows unlimited access to, at the time of writing, more than 1.5 million titles, including hundreds of thousands of titles in various foreign languages. If the content not found or just blank you must refresh this page
Unstructured Data Analytics
DOWNLOAD
Author : Jean Paul Isson
language : en
Publisher: John Wiley & Sons
Release Date : 2018-03-13
Unstructured Data Analytics written by Jean Paul Isson and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-03-13 with Computers categories.
Turn unstructured data into valuable business insight Unstructured Data Analytics provides an accessible, non-technical introduction to the analysis of unstructured data. Written by global experts in the analytics space, this book presents unstructured data analysis (UDA) concepts in a practical way, highlighting the broad scope of applications across industries, companies, and business functions. The discussion covers key aspects of UDA implementation, beginning with an explanation of the data and the information it provides, then moving into a holistic framework for implementation. Case studies show how real-world companies are leveraging UDA in security and customer management, and provide clear examples of both traditional business applications and newer, more innovative practices. Roughly 80 percent of today's data is unstructured in the form of emails, chats, social media, audio, and video. These data assets contain a wealth of valuable information that can be used to great advantage, but accessing that data in a meaningful way remains a challenge for many companies. This book provides the baseline knowledge and the practical understanding companies need to put this data to work. Supported by research with several industry leaders and packed with frontline stories from leading organizations such as Google, Amazon, Spotify, LinkedIn, Pfizer Manulife, AXA, Monster Worldwide, Under Armour, the Houston Rockets, DELL, IBM, and SAS Institute, this book provide a framework for building and implementing a successful UDA center of excellence. You will learn: How to increase Customer Acquisition and Customer Retention with UDA The Power of UDA for Fraud Detection and Prevention The Power of UDA in Human Capital Management & Human Resource The Power of UDA in Health Care and Medical Research The Power of UDA in National Security The Power of UDA in Legal Services The Power of UDA for product development The Power of UDA in Sports The future of UDA From small businesses to large multinational organizations, unstructured data provides the opportunity to gain consumer information straight from the source. Data is only as valuable as it is useful, and a robust, effective UDA strategy is the first step toward gaining the full advantage. Unstructured Data Analytics lays this space open for examination, and provides a solid framework for beginning meaningful analysis.
Tapping Into Unstructured Data
DOWNLOAD
Author : William H. Inmon
language : en
Publisher: Pearson Education
Release Date : 2007-12-11
Tapping Into Unstructured Data written by William H. Inmon and has been published by Pearson Education this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007-12-11 with Business & Economics categories.
The Definitive Guide to Unstructured Data Management and Analysis--From the World’s Leading Information Management Expert A wealth of invaluable information exists in unstructured textual form, but organizations have found it difficult or impossible to access and utilize it. This is changing rapidly: new approaches finally make it possible to glean useful knowledge from virtually any collection of unstructured data. William H. Inmon--the father of data warehousing--and Anthony Nesavich introduce the next data revolution: unstructured data management. Inmon and Nesavich cover all you need to know to make unstructured data work for your organization. You’ll learn how to bring it into your existing structured data environment, leverage existing analytical infrastructure, and implement textual analytic processing technologies to solve new problems and uncover new opportunities. Inmon and Nesavich introduce breakthrough techniques covered in no other book--including the powerful role of textual integration, new ways to integrate textual data into data warehouses, and new SQL techniques for reading and analyzing text. They also present five chapter-length, real-world case studies--demonstrating unstructured data at work in medical research, insurance, chemical manufacturing, contracting, and beyond. This book will be indispensable to every business and technical professional trying to make sense of a large body of unstructured text: managers, database designers, data modelers, DBAs, researchers, and end users alike. Coverage includes What unstructured data is, and how it differs from structured data First generation technology for handling unstructured data, from search engines to ECM--and its limitations Integrating text so it can be analyzed with a common, colloquial vocabulary: integration engines, ontologies, glossaries, and taxonomies Processing semistructured data: uncovering patterns, words, identifiers, and conflicts Novel processing opportunities that arise when text is freed from context Architecture and unstructured data: Data Warehousing 2.0 Building unstructured relational databases and linking them to structured data Visualizations and Self-Organizing Maps (SOMs), including Compudigm and Raptor solutions Capturing knowledge from spreadsheet data and email Implementing and managing metadata: data models, data quality, and more
Ecm Methods
DOWNLOAD
Author : Tom Jenkins
language : en
Publisher: Open Text Corporation
Release Date : 2005
Ecm Methods written by Tom Jenkins and has been published by Open Text Corporation this book supported file pdf, txt, epub, kindle and other format this book has been release on 2005 with Business enterprises categories.
Beschrijving van de informatietechnologie waarmee alle digitale informatie binnen een onderneming effectief verwerkt wordt waardoor zo optimaal mogelijk van die informatie gebruik kan worden gemaakt.
Building A Data Warehouse
DOWNLOAD
Author : Vincent Rainardi
language : en
Publisher: Apress
Release Date : 2008-03-11
Building A Data Warehouse written by Vincent Rainardi and has been published by Apress this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008-03-11 with Computers categories.
Building a Data Warehouse: With Examples in SQL Server describes how to build a data warehouse completely from scratch and shows practical examples on how to do it. Author Vincent Rainardi also describes some practical issues he has experienced that developers are likely to encounter in their first data warehousing project, along with solutions and advice. The relational database management system (RDBMS) used in the examples is SQL Server; the version will not be an issue as long as the user has SQL Server 2005 or later. The book is organized as follows. In the beginning of this book (chapters 1 through 6), you learn how to build a data warehouse, for example, defining the architecture, understanding the methodology, gathering the requirements, designing the data models, and creating the databases. Then in chapters 7 through 10, you learn how to populate the data warehouse, for example, extracting from source systems, loading the data stores, maintaining data quality, and utilizing the metadata. After you populate the data warehouse, in chapters 11 through 15, you explore how to present data to users using reports and multidimensional databases and how to use the data in the data warehouse for business intelligence, customer relationship management, and other purposes. Chapters 16 and 17 wrap up the book: After you have built your data warehouse, before it can be released to production, you need to test it thoroughly. After your application is in production, you need to understand how to administer data warehouse operation.
Managing Multimedia And Unstructured Data In The Oracle Database
DOWNLOAD
Author : Marcelle Kratochvil
language : en
Publisher: Packt Publishing Ltd
Release Date : 2013-03-21
Managing Multimedia And Unstructured Data In The Oracle Database written by Marcelle Kratochvil and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-03-21 with Computers categories.
This book is written in simple, easy to understand format with lots of screenshots and step-by-step explanations. If you are an Oracle database administrator, Museum curator, IT manager, Developer, Photographer, Intelligence team member, Warehouse or Software Architect then this book is for you. It covers the basics and then moves to advanced concepts. This will challenge and increase your knowledge enabling all those who read it to gain a greater understanding of multimedia and how all unstructured data is managed.
Big Data
DOWNLOAD
Author : Parvati Mishra
language : en
Publisher: Educohack Press
Release Date : 2025-01-07
Big Data written by Parvati Mishra and has been published by Educohack Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-01-07 with Computers categories.
The illustrations in this book are created by “Team Educohack”. Big Data: Revolutionizing the Future delves into how big data has become a dominant paradigm, transforming various sectors and reshaping society. This book, divided into 13 chapters, provides a thorough examination of big data, discussing its applications, growth, and potential. We explore how big data approaches can revolutionize both business and health sectors, while also addressing the risks associated with datafication. Chapters 11 to 13 focus on the growth of big data in different sectors, detailing the expanding market and advancements in big data analytics. Chapters 5 to 10 offer insightful examples of big data's transformative potential. This book emphasizes the importance of grounding these perspectives in existing scientific methods to enhance their practical applicability. We also discuss the comprehensive understanding that comes from analyzing all available data, illustrating this with empirical examples. Big Data: Revolutionizing the Future presents a clear, accessible narrative, enriched with a wide range of examples, to help readers grasp the full implications and opportunities of big data.
Spark For Data Science
DOWNLOAD
Author : Srinivas Duvvuri
language : en
Publisher: Packt Publishing Ltd
Release Date : 2016-09-30
Spark For Data Science written by Srinivas Duvvuri and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-09-30 with Computers categories.
Analyze your data and delve deep into the world of machine learning with the latest Spark version, 2.0 About This Book Perform data analysis and build predictive models on huge datasets that leverage Apache Spark Learn to integrate data science algorithms and techniques with the fast and scalable computing features of Spark to address big data challenges Work through practical examples on real-world problems with sample code snippets Who This Book Is For This book is for anyone who wants to leverage Apache Spark for data science and machine learning. If you are a technologist who wants to expand your knowledge to perform data science operations in Spark, or a data scientist who wants to understand how algorithms are implemented in Spark, or a newbie with minimal development experience who wants to learn about Big Data Analytics, this book is for you! What You Will Learn Consolidate, clean, and transform your data acquired from various data sources Perform statistical analysis of data to find hidden insights Explore graphical techniques to see what your data looks like Use machine learning techniques to build predictive models Build scalable data products and solutions Start programming using the RDD, DataFrame and Dataset APIs Become an expert by improving your data analytical skills In Detail This is the era of Big Data. The words ҂ig Data' implies big innovation and enables a competitive advantage for businesses. Apache Spark was designed to perform Big Data analytics at scale, and so Spark is equipped with the necessary algorithms and supports multiple programming languages. Whether you are a technologist, a data scientist, or a beginner to Big Data analytics, this book will provide you with all the skills necessary to perform statistical data analysis, data visualization, predictive modeling, and build scalable data products or solutions using Python, Scala, and R. With ample case studies and real-world examples, Spark for Data Science will help you ensure the successful execution of your data science projects. Style and approach This book takes a step-by-step approach to statistical analysis and machine learning, and is explained in a conversational and easy-to-follow style. Each topic is explained sequentially with a focus on the fundamentals as well as the advanced concepts of algorithms and techniques. Real-world examples with sample code snippets are also included.
Text Mining
DOWNLOAD
Author : Sholom M. Weiss
language : en
Publisher: Springer Science & Business Media
Release Date : 2010-01-08
Text Mining written by Sholom M. Weiss and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-01-08 with Computers categories.
Data mining is a mature technology. The prediction problem, looking for predictive patterns in data, has been widely studied. Strong me- ods are available to the practitioner. These methods process structured numerical information, where uniform measurements are taken over a sample of data. Text is often described as unstructured information. So, it would seem, text and numerical data are different, requiring different methods. Or are they? In our view, a prediction problem can be solved by the same methods, whether the data are structured - merical measurements or unstructured text. Text and documents can be transformed into measured values, such as the presence or absence of words, and the same methods that have proven successful for pred- tive data mining can be applied to text. Yet, there are key differences. Evaluation techniques must be adapted to the chronological order of publication and to alternative measures of error. Because the data are documents, more specialized analytical methods may be preferred for text. Moreover, the methods must be modi?ed to accommodate very high dimensions: tens of thousands of words and documents. Still, the central themes are similar.
Splunk Best Practices
DOWNLOAD
Author : Travis Marlette
language : en
Publisher: Packt Publishing Ltd
Release Date : 2016-09-21
Splunk Best Practices written by Travis Marlette and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-09-21 with Computers categories.
Design, implement, and publish custom Splunk applications by following best practices About This Book This is the most up-to-date guide on the market and will help you finish your tasks faster, easier, and more efficiently. Highly practical guide that addresses common and not-so-common pain points in Splunk. Want to explore shortcuts to perform tasks more efficiently with Splunk? This is the book for you! Who This Book Is For This book is for administrators, developers, and search ninjas who have been using Splunk for some time. A comprehensive coverage makes this book great for Splunk veterans and newbies alike. What You Will Learn Use Splunk effectively to gather, analyze, and report on operational data throughout your environment Expedite your reporting, and be empowered to present data in a meaningful way Create robust searches, reports, and charts using Splunk Modularize your programs for better reusability. Build your own Splunk apps and learn why they are important Learn how to integrate with enterprise systems Summarize data for longer term trending, reporting, and analysis In Detail This book will give you an edge over others through insights that will help you in day-to-day instances. When you're working with data from various sources in Splunk and performing analysis on this data, it can be a bit tricky. With this book, you will learn the best practices of working with Splunk. You'll learn about tools and techniques that will ease your life with Splunk, and will ultimately save you time. In some cases, it will adjust your thinking of what Splunk is, and what it can and cannot do. To start with, you'll get to know the best practices to get data into Splunk, analyze data, and package apps for distribution. Next, you'll discover the best practices in logging, operations, knowledge management, searching, and reporting. To finish off, we will teach you how to troubleshoot Splunk searches, as well as deployment, testing, and development with Splunk. Style and approach If you're stuck or want to find a better way to work with Splunk environment, this book will come handy. This easy-to-follow, insightful book contains step-by-step instructions and examples and scenarios that you will connect to.
Cognitive Science Computational Intelligence And Data Analytics
DOWNLOAD
Author : Vikas Khare
language : en
Publisher: Elsevier
Release Date : 2024-06-06
Cognitive Science Computational Intelligence And Data Analytics written by Vikas Khare and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-06-06 with Computers categories.
Cognitive Science, Computational Intelligence, and Data Analytics: Methods and Applications with Python introduces readers to the foundational concepts of data analysis, cognitive science, and computational intelligence, including AI and Machine Learning. The book's focus is on fundamental ideas, procedures, and computational intelligence tools that can be applied to a wide range of data analysis approaches, with applications that include mathematical programming, evolutionary simulation, machine learning, and logic-based models. It offers readers the fundamental and practical aspects of cognitive science and data analysis, exploring data analytics in terms of description, evolution, and applicability in real-life problems.The authors cover the history and evolution of cognitive analytics, methodological concerns in philosophy, syntax and semantics, understanding of generative linguistics, theory of memory and processing theory, structured and unstructured data, qualitative and quantitative data, measurement of variables, nominal, ordinals, intervals, and ratio scale data. The content in this book is tailored to the reader's needs in terms of both type and fundamentals, including coverage of multivariate analysis, CRISP methodology and SEMMA methodology. Each chapter provides practical, hands-on learning with real-world applications, including case studies and Python programs related to the key concepts being presented. - Demystifies the theory of data analytics using a step-by-step approach - Covers the intersection of cognitive science, computational intelligence, and data analytics by providing examples and case studies with applied algorithms, mathematics, and Python programming code - Introduces foundational data analytics techniques such as CRISP-DM, SEMMA, and Object Detection Models in the context of computational intelligence methods and tools - Covers key concepts of multivariate and cognitive data analytics such as factor analytics, principal component analytics, linear regression analysis, logistic regression analysis, and value chain applications