Author: Bart Czernicki
Publisher: Apress
ISBN: 1430224886
Category : Computers
Languages : en
Pages : 435
Book Description
Business intelligence (BI) software is the code and tools that allow you to view different components of a business using a single visual platform, making comprehending mountains of data easier. Applications that include reports, analytics, statistics, and historical and predictive modeling are all examples of BI applications. Currently, we are in the second generation of BI software, called BI 2.0. This generation is focused on writing BI software that is predictive, adaptive, simple, and interactive. As computers and software have evolved, more data can be presented to end users with increasingly visually rich techniques. Rich Internet application (RIA) technologies such as Microsoft Silverlight can be used to transform traditional user interfaces filled with boring data into fully interactive analytical applications to deliver insight from large data sets quickly. Furthermore, RIAs include 3D spatial design capabilities that allow for interesting layouts of aggregated data beyond a simple list or grid. BI 2.0 implemented via RIA technology can truly bring out the power of BI and deliver it to an average user via the Web. Next-Generation Business Intelligence Software with Rich Internet Applications provides developers, designers, and architects a solid foundation of BI design and architecture concepts with Microsoft Silverlight. This book covers key BI design concepts and how they can be applied without requiring an existing BI infrastructure. The author, Bart Czernicki, will show you how to build small BI applications by example that are interactive, highly visual, statistical, predictive, and most importantly, intuitive to the user. BI isn't just for the executive branch of a Fortune 500 company; it is for the masses. Let Next-Generation Business Intelligence Software with Rich Internet Applications show you how to unlock the rich intelligence you already have.
Next-Generation Business Intelligence Software with Silverlight 3
Author: Bart Czernicki
Publisher: Apress
ISBN: 1430224886
Category : Computers
Languages : en
Pages : 435
Book Description
Business intelligence (BI) software is the code and tools that allow you to view different components of a business using a single visual platform, making comprehending mountains of data easier. Applications that include reports, analytics, statistics, and historical and predictive modeling are all examples of BI applications. Currently, we are in the second generation of BI software, called BI 2.0. This generation is focused on writing BI software that is predictive, adaptive, simple, and interactive. As computers and software have evolved, more data can be presented to end users with increasingly visually rich techniques. Rich Internet application (RIA) technologies such as Microsoft Silverlight can be used to transform traditional user interfaces filled with boring data into fully interactive analytical applications to deliver insight from large data sets quickly. Furthermore, RIAs include 3D spatial design capabilities that allow for interesting layouts of aggregated data beyond a simple list or grid. BI 2.0 implemented via RIA technology can truly bring out the power of BI and deliver it to an average user via the Web. Next-Generation Business Intelligence Software with Rich Internet Applications provides developers, designers, and architects a solid foundation of BI design and architecture concepts with Microsoft Silverlight. This book covers key BI design concepts and how they can be applied without requiring an existing BI infrastructure. The author, Bart Czernicki, will show you how to build small BI applications by example that are interactive, highly visual, statistical, predictive, and most importantly, intuitive to the user. BI isn't just for the executive branch of a Fortune 500 company; it is for the masses. Let Next-Generation Business Intelligence Software with Rich Internet Applications show you how to unlock the rich intelligence you already have.
Publisher: Apress
ISBN: 1430224886
Category : Computers
Languages : en
Pages : 435
Book Description
Business intelligence (BI) software is the code and tools that allow you to view different components of a business using a single visual platform, making comprehending mountains of data easier. Applications that include reports, analytics, statistics, and historical and predictive modeling are all examples of BI applications. Currently, we are in the second generation of BI software, called BI 2.0. This generation is focused on writing BI software that is predictive, adaptive, simple, and interactive. As computers and software have evolved, more data can be presented to end users with increasingly visually rich techniques. Rich Internet application (RIA) technologies such as Microsoft Silverlight can be used to transform traditional user interfaces filled with boring data into fully interactive analytical applications to deliver insight from large data sets quickly. Furthermore, RIAs include 3D spatial design capabilities that allow for interesting layouts of aggregated data beyond a simple list or grid. BI 2.0 implemented via RIA technology can truly bring out the power of BI and deliver it to an average user via the Web. Next-Generation Business Intelligence Software with Rich Internet Applications provides developers, designers, and architects a solid foundation of BI design and architecture concepts with Microsoft Silverlight. This book covers key BI design concepts and how they can be applied without requiring an existing BI infrastructure. The author, Bart Czernicki, will show you how to build small BI applications by example that are interactive, highly visual, statistical, predictive, and most importantly, intuitive to the user. BI isn't just for the executive branch of a Fortune 500 company; it is for the masses. Let Next-Generation Business Intelligence Software with Rich Internet Applications show you how to unlock the rich intelligence you already have.
Next Generation Business Intelligence
Author: Sonar, Rajendra M.
Publisher: Vikas Publishing House
ISBN: 8125942564
Category :
Languages : en
Pages : 240
Book Description
Business Intelligence (BI) has been successfully deployed by modern businesses to serve their customers and stakeholders. However, organizations increasingly look at BI to be all pervasive and realize its higher level of potential, instead of following it conventionally. The book covers the techniques, technologies and frameworks that can be used to build next generation BI.
Publisher: Vikas Publishing House
ISBN: 8125942564
Category :
Languages : en
Pages : 240
Book Description
Business Intelligence (BI) has been successfully deployed by modern businesses to serve their customers and stakeholders. However, organizations increasingly look at BI to be all pervasive and realize its higher level of potential, instead of following it conventionally. The book covers the techniques, technologies and frameworks that can be used to build next generation BI.
Business Intelligence for New-Generation Managers
Author: Jörg H. Mayer
Publisher: Springer
ISBN: 3319156969
Category : Business & Economics
Languages : en
Pages : 141
Book Description
Executives in Europe have significantly expanded their role in operations – in parallel to their strategic leadership. At the same time, they need to make decisions faster than in the past. In these demanding times, a redesigned Business Intelligence (BI) should support managers in their new roles. This book summarizes current avenues of development helping managers to perform their jobs more productively by using 'BI for managers' as their central, hands-on, day-to-day source of information – even when they are mobile.
Publisher: Springer
ISBN: 3319156969
Category : Business & Economics
Languages : en
Pages : 141
Book Description
Executives in Europe have significantly expanded their role in operations – in parallel to their strategic leadership. At the same time, they need to make decisions faster than in the past. In these demanding times, a redesigned Business Intelligence (BI) should support managers in their new roles. This book summarizes current avenues of development helping managers to perform their jobs more productively by using 'BI for managers' as their central, hands-on, day-to-day source of information – even when they are mobile.
Disruptive Analytics
Author: Thomas W. Dinsmore
Publisher: Apress
ISBN: 1484213114
Category : Computers
Languages : en
Pages : 276
Book Description
Learn all you need to know about seven key innovations disrupting business analytics today. These innovations—the open source business model, cloud analytics, the Hadoop ecosystem, Spark and in-memory analytics, streaming analytics, Deep Learning, and self-service analytics—are radically changing how businesses use data for competitive advantage. Taken together, they are disrupting the business analytics value chain, creating new opportunities. Enterprises who seize the opportunity will thrive and prosper, while others struggle and decline: disrupt or be disrupted. Disruptive Business Analytics provides strategies to profit from disruption. It shows you how to organize for insight, build and provision an open source stack, how to practice lean data warehousing, and how to assimilate disruptive innovations into an organization. Through a short history of business analytics and a detailed survey of products and services, analytics authority Thomas W. Dinsmore provides a practical explanation of the most compelling innovations available today. What You'll Learn Discover how the open source business model works and how to make it work for you See how cloud computing completely changes the economics of analytics Harness the power of Hadoop and its ecosystem Find out why Apache Spark is everywhere Discover the potential of streaming and real-time analytics Learn what Deep Learning can do and why it matters See how self-service analytics can change the way organizations do business Who This Book Is For Corporate actors at all levels of responsibility for analytics: analysts, CIOs, CTOs, strategic decision makers, managers, systems architects, technical marketers, product developers, IT personnel, and consultants.
Publisher: Apress
ISBN: 1484213114
Category : Computers
Languages : en
Pages : 276
Book Description
Learn all you need to know about seven key innovations disrupting business analytics today. These innovations—the open source business model, cloud analytics, the Hadoop ecosystem, Spark and in-memory analytics, streaming analytics, Deep Learning, and self-service analytics—are radically changing how businesses use data for competitive advantage. Taken together, they are disrupting the business analytics value chain, creating new opportunities. Enterprises who seize the opportunity will thrive and prosper, while others struggle and decline: disrupt or be disrupted. Disruptive Business Analytics provides strategies to profit from disruption. It shows you how to organize for insight, build and provision an open source stack, how to practice lean data warehousing, and how to assimilate disruptive innovations into an organization. Through a short history of business analytics and a detailed survey of products and services, analytics authority Thomas W. Dinsmore provides a practical explanation of the most compelling innovations available today. What You'll Learn Discover how the open source business model works and how to make it work for you See how cloud computing completely changes the economics of analytics Harness the power of Hadoop and its ecosystem Find out why Apache Spark is everywhere Discover the potential of streaming and real-time analytics Learn what Deep Learning can do and why it matters See how self-service analytics can change the way organizations do business Who This Book Is For Corporate actors at all levels of responsibility for analytics: analysts, CIOs, CTOs, strategic decision makers, managers, systems architects, technical marketers, product developers, IT personnel, and consultants.
Perspectives on Business Intelligence
Author: Raymond T. Ng
Publisher: Springer Nature
ISBN: 3031018486
Category : Computers
Languages : en
Pages : 151
Book Description
In the 1980s, traditional Business Intelligence (BI) systems focused on the delivery of reports that describe the state of business activities in the past, such as for questions like "How did our sales perform during the last quarter?" A decade later, there was a shift to more interactive content that presented how the business was performing at the present time, answering questions like "How are we doing right now?" Today the focus of BI users are looking into the future. "Given what I did before and how I am currently doing this quarter, how will I do next quarter?" Furthermore, fuelled by the demands of Big Data, BI systems are going through a time of incredible change. Predictive analytics, high volume data, unstructured data, social data, mobile, consumable analytics, and data visualization are all examples of demands and capabilities that have become critical within just the past few years, and are growing at an unprecedented pace. This book introduces research problems and solutions on various aspects central to next-generation BI systems. It begins with a chapter on an industry perspective on how BI has evolved, and discusses how game-changing trends have drastically reshaped the landscape of BI. One of the game changers is the shift toward the consumerization of BI tools. As a result, for BI tools to be successfully used by business users (rather than IT departments), the tools need a business model, rather than a data model. One chapter of the book surveys four different types of business modeling. However, even with the existence of a business model for users to express queries, the data that can meet the needs are still captured within a data model. The next chapter on vivification addresses the problem of closing the gap, which is often significant, between the business and the data models. Moreover, Big Data forces BI systems to integrate and consolidate multiple, and often wildly different, data sources. One chapter gives an overview of several integration architectures for dealing with the challenges that need to be overcome. While the book so far focuses on the usual structured relational data, the remaining chapters turn to unstructured data, an ever-increasing and important component of Big Data. One chapter on information extraction describes methods for dealing with the extraction of relations from free text and the web. Finally, BI users need tools to visualize and interpret new and complex types of information in a way that is compelling, intuitive, but accurate. The last chapter gives an overview of information visualization for decision support and text.
Publisher: Springer Nature
ISBN: 3031018486
Category : Computers
Languages : en
Pages : 151
Book Description
In the 1980s, traditional Business Intelligence (BI) systems focused on the delivery of reports that describe the state of business activities in the past, such as for questions like "How did our sales perform during the last quarter?" A decade later, there was a shift to more interactive content that presented how the business was performing at the present time, answering questions like "How are we doing right now?" Today the focus of BI users are looking into the future. "Given what I did before and how I am currently doing this quarter, how will I do next quarter?" Furthermore, fuelled by the demands of Big Data, BI systems are going through a time of incredible change. Predictive analytics, high volume data, unstructured data, social data, mobile, consumable analytics, and data visualization are all examples of demands and capabilities that have become critical within just the past few years, and are growing at an unprecedented pace. This book introduces research problems and solutions on various aspects central to next-generation BI systems. It begins with a chapter on an industry perspective on how BI has evolved, and discusses how game-changing trends have drastically reshaped the landscape of BI. One of the game changers is the shift toward the consumerization of BI tools. As a result, for BI tools to be successfully used by business users (rather than IT departments), the tools need a business model, rather than a data model. One chapter of the book surveys four different types of business modeling. However, even with the existence of a business model for users to express queries, the data that can meet the needs are still captured within a data model. The next chapter on vivification addresses the problem of closing the gap, which is often significant, between the business and the data models. Moreover, Big Data forces BI systems to integrate and consolidate multiple, and often wildly different, data sources. One chapter gives an overview of several integration architectures for dealing with the challenges that need to be overcome. While the book so far focuses on the usual structured relational data, the remaining chapters turn to unstructured data, an ever-increasing and important component of Big Data. One chapter on information extraction describes methods for dealing with the extraction of relations from free text and the web. Finally, BI users need tools to visualize and interpret new and complex types of information in a way that is compelling, intuitive, but accurate. The last chapter gives an overview of information visualization for decision support and text.
Internet of Things and Big Data Analytics Toward Next-Generation Intelligence
Author: Nilanjan Dey
Publisher: Springer
ISBN: 331960435X
Category : Technology & Engineering
Languages : en
Pages : 545
Book Description
This book highlights state-of-the-art research on big data and the Internet of Things (IoT), along with related areas to ensure efficient and Internet-compatible IoT systems. It not only discusses big data security and privacy challenges, but also energy-efficient approaches to improving virtual machine placement in cloud computing environments. Big data and the Internet of Things (IoT) are ultimately two sides of the same coin, yet extracting, analyzing and managing IoT data poses a serious challenge. Accordingly, proper analytics infrastructures/platforms should be used to analyze IoT data. Information technology (IT) allows people to upload, retrieve, store and collect information, which ultimately forms big data. The use of big data analytics has grown tremendously in just the past few years. At the same time, the IoT has entered the public consciousness, sparking people’s imaginations as to what a fully connected world can offer. Further, the book discusses the analysis of real-time big data to derive actionable intelligence in enterprise applications in several domains, such as in industry and agriculture. It explores possible automated solutions in daily life, including structures for smart cities and automated home systems based on IoT technology, as well as health care systems that manage large amounts of data (big data) to improve clinical decisions. The book addresses the security and privacy of the IoT and big data technologies, while also revealing the impact of IoT technologies on several scenarios in smart cities design. Intended as a comprehensive introduction, it offers in-depth analysis and provides scientists, engineers and professionals the latest techniques, frameworks and strategies used in IoT and big data technologies.
Publisher: Springer
ISBN: 331960435X
Category : Technology & Engineering
Languages : en
Pages : 545
Book Description
This book highlights state-of-the-art research on big data and the Internet of Things (IoT), along with related areas to ensure efficient and Internet-compatible IoT systems. It not only discusses big data security and privacy challenges, but also energy-efficient approaches to improving virtual machine placement in cloud computing environments. Big data and the Internet of Things (IoT) are ultimately two sides of the same coin, yet extracting, analyzing and managing IoT data poses a serious challenge. Accordingly, proper analytics infrastructures/platforms should be used to analyze IoT data. Information technology (IT) allows people to upload, retrieve, store and collect information, which ultimately forms big data. The use of big data analytics has grown tremendously in just the past few years. At the same time, the IoT has entered the public consciousness, sparking people’s imaginations as to what a fully connected world can offer. Further, the book discusses the analysis of real-time big data to derive actionable intelligence in enterprise applications in several domains, such as in industry and agriculture. It explores possible automated solutions in daily life, including structures for smart cities and automated home systems based on IoT technology, as well as health care systems that manage large amounts of data (big data) to improve clinical decisions. The book addresses the security and privacy of the IoT and big data technologies, while also revealing the impact of IoT technologies on several scenarios in smart cities design. Intended as a comprehensive introduction, it offers in-depth analysis and provides scientists, engineers and professionals the latest techniques, frameworks and strategies used in IoT and big data technologies.
Transactions on Large-Scale Data- and Knowledge-Centered Systems XXXVII
Author: Abdelkader Hameurlain
Publisher: Springer
ISBN: 3662579324
Category : Computers
Languages : en
Pages : 200
Book Description
This, the 37th issue of Transactions on Large-Scale Data- and Knowledge-Centered Systems, contains five revised selected regular papers. Topics covered include data security in clouds, privacy languages, probabilistic modelling in linked data integration, business intelligence based on multi-agent systems, collaborative filtering, and prediction accuracy.
Publisher: Springer
ISBN: 3662579324
Category : Computers
Languages : en
Pages : 200
Book Description
This, the 37th issue of Transactions on Large-Scale Data- and Knowledge-Centered Systems, contains five revised selected regular papers. Topics covered include data security in clouds, privacy languages, probabilistic modelling in linked data integration, business intelligence based on multi-agent systems, collaborative filtering, and prediction accuracy.
Enabling Real-Time Business Intelligence
Author: Malu Castellanos
Publisher: Springer
ISBN: 3662468395
Category : Computers
Languages : en
Pages : 194
Book Description
This book constitutes the thoroughly refereed conference proceedings of the 7th International Workshop on Business Intelligence for the Real-Time Enterprise, BIRTE 2013, held in Riva del Garda, Italy, in August 2013 and of the 8th International Workshop on Business Intelligence for the Real-Time Enterprise, BIRTE 2014, held in Hangzhou, China, in September 2014, in conjunction with VLDB 2013 and 2014, the International Conference on Very Large Data Bases. The BIRTE workshop series provides a forum for the discussion and advancement of the science and engineering enabling real-time business intelligence and the novel applications that build on these foundational techniques. This volume contains five full, two short, and two demo papers, which were carefully reviewed and selected with an acceptance rate of 45%. In addition, one keynote and three invited papers are included.
Publisher: Springer
ISBN: 3662468395
Category : Computers
Languages : en
Pages : 194
Book Description
This book constitutes the thoroughly refereed conference proceedings of the 7th International Workshop on Business Intelligence for the Real-Time Enterprise, BIRTE 2013, held in Riva del Garda, Italy, in August 2013 and of the 8th International Workshop on Business Intelligence for the Real-Time Enterprise, BIRTE 2014, held in Hangzhou, China, in September 2014, in conjunction with VLDB 2013 and 2014, the International Conference on Very Large Data Bases. The BIRTE workshop series provides a forum for the discussion and advancement of the science and engineering enabling real-time business intelligence and the novel applications that build on these foundational techniques. This volume contains five full, two short, and two demo papers, which were carefully reviewed and selected with an acceptance rate of 45%. In addition, one keynote and three invited papers are included.
Web Services: Concepts, Methodologies, Tools, and Applications
Author: Management Association, Information Resources
Publisher: IGI Global
ISBN: 1522575022
Category : Computers
Languages : en
Pages : 2362
Book Description
Web service technologies are redefining the way that large and small companies are doing business and exchanging information. Due to the critical need for furthering automation, engagement, and efficiency, systems and workflows are becoming increasingly more web-based. Web Services: Concepts, Methodologies, Tools, and Applications is an innovative reference source that examines relevant theoretical frameworks, current practice guidelines, industry standards and standardization, and the latest empirical research findings in web services. Highlighting a range of topics such as cloud computing, quality of service, and semantic web, this multi-volume book is designed for computer engineers, IT specialists, software designers, professionals, researchers, and upper-level students interested in web services architecture, frameworks, and security.
Publisher: IGI Global
ISBN: 1522575022
Category : Computers
Languages : en
Pages : 2362
Book Description
Web service technologies are redefining the way that large and small companies are doing business and exchanging information. Due to the critical need for furthering automation, engagement, and efficiency, systems and workflows are becoming increasingly more web-based. Web Services: Concepts, Methodologies, Tools, and Applications is an innovative reference source that examines relevant theoretical frameworks, current practice guidelines, industry standards and standardization, and the latest empirical research findings in web services. Highlighting a range of topics such as cloud computing, quality of service, and semantic web, this multi-volume book is designed for computer engineers, IT specialists, software designers, professionals, researchers, and upper-level students interested in web services architecture, frameworks, and security.
Principles Of Data Science
Author: Ambrish Kumar Sharma
Publisher: AG PUBLISHING HOUSE (AGPH Books)
ISBN: 9395936401
Category : Study Aids
Languages : en
Pages : 234
Book Description
With the advent of the "big data" era, the necessity for secure data storage has risen. To solve the problem of data storage, the main emphasis was on building a framework. The key ingredient is data science. Data Science is an interdisciplinary field that applies statistical methods, computer science, and other disciplines to raw data to conclude the world. Data is a crucial part of every business since it provides the information upon which wise business choices may be made. To deal with the growing volume of data, the interdisciplinary subject of data science emerged. It employs rigorous methods, protocols, algorithms, and frameworks from the scientific community to mine vast stores of data for useful information. Both structured and unstructured information may be extracted. To understand and analyse real-world events using data, a field known as "data science" has emerged to bring together concepts, data analysis, Machine Learning, and related methodologies. Data science is a term for a wide range of subfields within the study of data analysis. Data Science is a broad discipline that draws upon many disciplines' theories, practices, and tools, including but not limited to statistics, information science, mathematics, and computer science. Data scientists use many different methods, such as machine learning, data visualization, pattern recognition, probability modelling, signal processing, data engineering, etc
Publisher: AG PUBLISHING HOUSE (AGPH Books)
ISBN: 9395936401
Category : Study Aids
Languages : en
Pages : 234
Book Description
With the advent of the "big data" era, the necessity for secure data storage has risen. To solve the problem of data storage, the main emphasis was on building a framework. The key ingredient is data science. Data Science is an interdisciplinary field that applies statistical methods, computer science, and other disciplines to raw data to conclude the world. Data is a crucial part of every business since it provides the information upon which wise business choices may be made. To deal with the growing volume of data, the interdisciplinary subject of data science emerged. It employs rigorous methods, protocols, algorithms, and frameworks from the scientific community to mine vast stores of data for useful information. Both structured and unstructured information may be extracted. To understand and analyse real-world events using data, a field known as "data science" has emerged to bring together concepts, data analysis, Machine Learning, and related methodologies. Data science is a term for a wide range of subfields within the study of data analysis. Data Science is a broad discipline that draws upon many disciplines' theories, practices, and tools, including but not limited to statistics, information science, mathematics, and computer science. Data scientists use many different methods, such as machine learning, data visualization, pattern recognition, probability modelling, signal processing, data engineering, etc