The document discusses a joint whitepaper from several major IT vendors that outlines a proposed common interface for configuration management database (CMDB) products to facilitate data federation. The whitepaper proposes services for CMDB administration, resource federation and reconciliation, resource querying, and subscription/notification to address key challenges around connecting diverse management data sources. While this cooperation is promising, open standards will be important to ensure interoperability and avoid vendor lock-in.
This document discusses a framework for virtual organizing in the digital age. It proposes that virtual organizing consists of three interdependent vectors: customer interaction, asset sourcing, and knowledge leverage. Each vector progresses through three stages - from a focus on task units, to the organizational level, to inter-organizational networks. An integrated IT platform is key to enabling the connections between these vectors and stages. The framework is presented as a new business model for companies to leverage virtual capabilities, rather than as a distinct organizational structure. Customer interaction involves remote experiences of products/services, dynamic customization, and customer communities.
- The document discusses various approaches to solving the problem of integrating data that resides across an enterprise in different locations and formats, including data foraging, data consolidation, data virtualization, and information fabrics.
- It presents a decision framework to help enterprises identify the best fitting approach for their specific needs and scenarios based on factors like data sources, usage scenarios, and technical requirements.
- Common usage scenarios discussed are advanced analytics and self-service business intelligence, where different approaches may be better suited depending on an organization's unique situation.
Forrester: How Organizations Are Improving Business Resiliency with Continuou...EMC
This analyst report describes reasons why adoption of continuous availability is rapidly increasing, citing research on benefits they believe they can realize in their IT environment.
On-premises, consumption-based private cloud creates opportunity for enterpri...Stanton Jones
The document discusses a new "on-premises, consumption-based private cloud" (OPCB) model for data storage that combines the benefits of public and private clouds. It provides flexibility and cost savings like public clouds through usage-based pricing, but with the security, control and data sovereignty of private clouds by hosting the infrastructure on-site. The OPCB model addresses enterprises' needs to reduce costs while the pace of data growth prevents waiting for public cloud issues to be resolved. It evaluates this model for customers who value data sovereignty and flexibility without full operational control of traditional private clouds.
Approximate Semantic Matching of Heterogeneous EventsEdward Curry
Event-based systems have loose coupling within space, time and synchronization, providing a scalable infrastructure for information exchange and distributed workflows. However, event-based systems are tightly coupled, via event subscriptions and patterns, to the semantics of the underlying event schema and values. The high degree of semantic heterogeneity of events in large and open deployments such as smart cities and the sensor web makes it difficult to develop and maintain event-based systems. In order to address semantic coupling within event-based systems, we propose vocabulary free subscriptions together with the use of approximate semantic matching of events. This paper examines the requirement of event semantic decoupling and discusses approximate semantic event matching and the consequences it implies for event processing systems. We introduce a semantic event matcher and evaluate the suitability of an approximate hybrid matcher based on both thesauri-based and distributional semantics-based similarity and relatedness measures. The matcher is evaluated over show that the approach matches a representation of Wikipedia and Freebase events. Initial evaluations events structured with maximal combined precision-recall F1 score of 75.89% on average in all experiments with a subscription set of 7 subscriptions. The evaluation shows how a hybrid approach to semantic event matching outperforms a single similarity measure approach.
Hasan S, O'Riain S, Curry E. Approximate Semantic Matching of Heterogeneous Events. In: 6th ACM International Conference on Distributed Event-Based Systems (DEBS 2012).
The New York Times is the largest metropolitan and the third largest newspaper in the United States. The Times website, nytimes.com, is ranked as the most
popular newspaper website in the United States and is an important source of advertisement revenue for the company. The NYT has a rich history for curation of its articles and its 100 year old curated repository has ultimately defined its participation as one of the first players in the emergingWeb of Data.
Data curation is a process that can ensure the quality of data and its fitness for use. Traditional approaches to curation are struggling with increased data volumes, and near real-time demands for curated data. In response, curation teams have turned to community crowd-sourcing and semi-automatedmetadata tools for assistance.
E. Curry, A. Freitas, and S. O’Riáin, “The Role of Community-Driven Data Curation for Enterprises,” in Linking Enterprise Data, D. Wood, Ed. Boston, MA: Springer US, 2010, pp. 25-47.
Developing an Sustainable IT Capability: Lessons From Intel's JourneyEdward Curry
Intel Corporation set itself a goal to reduce its global-warming greenhouse gas footprint by 20% by 2012 from 2007 levels. Through the use of sustainable IT, the Intel IT organization is recognized as a significant contributor to the company’s sustainability strategy by transforming its IT operations and overall Intel operations. This article describes how Intel has achieved IT sustainability benefits thus far by developing four key capabilities. These capabilities have been incorporated into the Sustainable ICT Capability Maturity Framework (SICT-CMF), a model developed by an industry consortium in which the authors were key participants. The article ends with lessons learned from Intel’s experiences that can be applied by business and IT executives in other enterprises.
The document discusses a joint whitepaper from several major IT vendors that outlines a proposed common interface for configuration management database (CMDB) products to facilitate data federation. The whitepaper proposes services for CMDB administration, resource federation and reconciliation, resource querying, and subscription/notification to address key challenges around connecting diverse management data sources. While this cooperation is promising, open standards will be important to ensure interoperability and avoid vendor lock-in.
This document discusses a framework for virtual organizing in the digital age. It proposes that virtual organizing consists of three interdependent vectors: customer interaction, asset sourcing, and knowledge leverage. Each vector progresses through three stages - from a focus on task units, to the organizational level, to inter-organizational networks. An integrated IT platform is key to enabling the connections between these vectors and stages. The framework is presented as a new business model for companies to leverage virtual capabilities, rather than as a distinct organizational structure. Customer interaction involves remote experiences of products/services, dynamic customization, and customer communities.
- The document discusses various approaches to solving the problem of integrating data that resides across an enterprise in different locations and formats, including data foraging, data consolidation, data virtualization, and information fabrics.
- It presents a decision framework to help enterprises identify the best fitting approach for their specific needs and scenarios based on factors like data sources, usage scenarios, and technical requirements.
- Common usage scenarios discussed are advanced analytics and self-service business intelligence, where different approaches may be better suited depending on an organization's unique situation.
Forrester: How Organizations Are Improving Business Resiliency with Continuou...EMC
This analyst report describes reasons why adoption of continuous availability is rapidly increasing, citing research on benefits they believe they can realize in their IT environment.
On-premises, consumption-based private cloud creates opportunity for enterpri...Stanton Jones
The document discusses a new "on-premises, consumption-based private cloud" (OPCB) model for data storage that combines the benefits of public and private clouds. It provides flexibility and cost savings like public clouds through usage-based pricing, but with the security, control and data sovereignty of private clouds by hosting the infrastructure on-site. The OPCB model addresses enterprises' needs to reduce costs while the pace of data growth prevents waiting for public cloud issues to be resolved. It evaluates this model for customers who value data sovereignty and flexibility without full operational control of traditional private clouds.
Approximate Semantic Matching of Heterogeneous EventsEdward Curry
Event-based systems have loose coupling within space, time and synchronization, providing a scalable infrastructure for information exchange and distributed workflows. However, event-based systems are tightly coupled, via event subscriptions and patterns, to the semantics of the underlying event schema and values. The high degree of semantic heterogeneity of events in large and open deployments such as smart cities and the sensor web makes it difficult to develop and maintain event-based systems. In order to address semantic coupling within event-based systems, we propose vocabulary free subscriptions together with the use of approximate semantic matching of events. This paper examines the requirement of event semantic decoupling and discusses approximate semantic event matching and the consequences it implies for event processing systems. We introduce a semantic event matcher and evaluate the suitability of an approximate hybrid matcher based on both thesauri-based and distributional semantics-based similarity and relatedness measures. The matcher is evaluated over show that the approach matches a representation of Wikipedia and Freebase events. Initial evaluations events structured with maximal combined precision-recall F1 score of 75.89% on average in all experiments with a subscription set of 7 subscriptions. The evaluation shows how a hybrid approach to semantic event matching outperforms a single similarity measure approach.
Hasan S, O'Riain S, Curry E. Approximate Semantic Matching of Heterogeneous Events. In: 6th ACM International Conference on Distributed Event-Based Systems (DEBS 2012).
The New York Times is the largest metropolitan and the third largest newspaper in the United States. The Times website, nytimes.com, is ranked as the most
popular newspaper website in the United States and is an important source of advertisement revenue for the company. The NYT has a rich history for curation of its articles and its 100 year old curated repository has ultimately defined its participation as one of the first players in the emergingWeb of Data.
Data curation is a process that can ensure the quality of data and its fitness for use. Traditional approaches to curation are struggling with increased data volumes, and near real-time demands for curated data. In response, curation teams have turned to community crowd-sourcing and semi-automatedmetadata tools for assistance.
E. Curry, A. Freitas, and S. O’Riáin, “The Role of Community-Driven Data Curation for Enterprises,” in Linking Enterprise Data, D. Wood, Ed. Boston, MA: Springer US, 2010, pp. 25-47.
Developing an Sustainable IT Capability: Lessons From Intel's JourneyEdward Curry
Intel Corporation set itself a goal to reduce its global-warming greenhouse gas footprint by 20% by 2012 from 2007 levels. Through the use of sustainable IT, the Intel IT organization is recognized as a significant contributor to the company’s sustainability strategy by transforming its IT operations and overall Intel operations. This article describes how Intel has achieved IT sustainability benefits thus far by developing four key capabilities. These capabilities have been incorporated into the Sustainable ICT Capability Maturity Framework (SICT-CMF), a model developed by an industry consortium in which the authors were key participants. The article ends with lessons learned from Intel’s experiences that can be applied by business and IT executives in other enterprises.
Wikipedia (DBpedia): Crowdsourced Data CurationEdward Curry
Wikipedia is an open-source encyclopedia, built collaboratively by a large community of web editors. The success of Wikipedia as one of the most important sources of information available today still challenges existing models of content creation. Despite the fact that the term ‘curation’ is not commonly addressed by Wikipedia’s contributors, the task of digital curation is the central activity of Wikipedia editors, who have the responsibility for information quality standards.
Wikipedia, is already widely used as a collaborative environment inside organizations5.
The investigation of the collaboration dynamics behind Wikipedia highlights important features and good practices which can be applied to different organizations. Our analysis focuses on the curation perspective and covers two important dimensions: social organization and artifacts, tools & processes for cooperative work coordination. These are key enablers that support the creation of high quality information products in Wikipedia’s decentralized environment.
Wolters Kluwer and Risk.Net present the current challenges, priorities and trends influencing banks’ investment in risktech and assesses how they can drive better value in the future. Survey report.
This document proposes a new framework called Actionable Knowledge As A Service (AKAAS) for managing knowledge in cloud computing environments. It discusses how traditional knowledge management systems are challenged by cloud computing and social/technological changes. The framework aims to provide on-demand, customizable knowledge to users based on their needs and interactions. It argues that user behaviors and needs should be the focus, rather than just the volume of published content. Analytics using data on user interactions are proposed to help discover knowledge tailored to specific contexts. The goal is to evolve from push-based knowledge delivery to personalized, actionable knowledge acquisition.
An Environmental Chargeback for Data Center and Cloud Computing ConsumersEdward Curry
Government, business, and the general public increasingly agree that the polluter should pay. Carbon dioxide and environmental damage are considered viable chargeable commodities. The net effect of this for data center and cloud computing operators is that they should look to “chargeback” the environmental impacts of their services to the consuming end-users. An environmental chargeback model can have a positive effect on environmental impacts by linking consumers to the indirect impacts of their usage, facilitating clearer understanding of the impact of their actions. In this paper we motivate the need for environmental chargeback mechanisms. The environmental chargeback model is described including requirements, methodology for definition, and environmental impact allocation strategies. The paper details a proof-of-concept within an operational data center together with discussion on experiences gained and future research directions.
Curry, E.; Hasan, S.; White, M.; and Melvin, H. 2012. An Environmental Chargeback for Data Center and Cloud Computing Consumers. In Huusko, J.; de Meer, H.; Klingert, S.; and Somov, A., eds., First International Workshop on Energy-Efficient Data Centers. Madrid, Spain: Springer Berlin / Heidelberg.
Ericsson Review: Data without borders: an information architecture for enterp...Ericsson
Today’s information systems rely on mediation to use and share the data that is available within an enterprise. But this is changing. IT systems are moving away from traditional architectures, where information is hidden inside functions, toward an information-centric approach that separates information from functionality – data without borders. Breaking functionality and information apart creates a systems architecture that is flexible, supports business agility, and ultimately boosts the bottom line.
Master data management (MDM) is defined as an application-independent process which describes, owns and manages core business data entities. The establishment of the MDM process is a Business Engineering (BE) tasks which requires organizational design. This paper reports on the results of a questionnaire survey among large enterprises aiming at delivering insight into what tasks and master data classes MDM organizations cover (“scope”) and how many people they employ (“size”). The nature of the study is descriptive, i.e. it allows for the identification of patterns and trends in organizing the MDM process.
Richard (Dick) Fisher
Organizations are creating data records at a pace few could have imagined just five years ago - terabytes (1 trillion bytes) now and heading toward petabytes (1,000 terabytes) that may need to be archived or disposed of! This session uses the requirement for archiving and disposition of PeopleSoft records and data elements as one example, plus other real world requirements.
Read more: http://www.rimeducation.com/videos/rimondemand.php
Challenges Ahead for Converging Financial DataEdward Curry
Consumers of financial information come in many guises from personal investors looking for that value for money share, to government regulators investigating corporate fraud, to business executives seeking competitive advantage over their competition. While the particular analysis performed by each of these information consumers will vary, they all have to deal with the explosion of information available from multiple sources including, SEC filings, corporate press releases, market press coverage, and expert commentary. Recent economic events have begun to bring sharp focus on the activities and actions of financial markets, institutions and not least regulatory authorities. Calls for enhanced scrutiny will bring increased regulation and information transparency While extracting information from individual filings is relatively easy to perform when a machine readable format is utilized (for example, using XBRL, the eXtensible Business Reporting Language), cross comparison of extracted financial information can be problematic as descriptions and accounting terms vary across companies and jurisdictions. Across multiple sources the problem becomes the classical data integration problem where a common data abstraction is necessary before functional data use can begin. Within this paper we discuss the challenges in converging financial data from multiple sources. We concentrate on integrating data from multiple sources in terms of the abstraction, linking, and consolidation activities needed to consolidate data before more sophisticated analysis algorithms can examine the data for the objectives of particular information consumers (for e.g. competitive analysis, regulatory compliance, or investor analysis). We base our discussion on several years researching and deploying data integration systems in both the web and enterprise environments.
E. Curry, A. Harth, and S. O’Riain, “Challenges Ahead for Converging Financial Data,” in Proceedings of the XBRL/W3C Workshop on Improving Access to Financial Data on the Web, 2009.
How to mitigate risk in the age of the cloudJames Sankar
The convergence of mobile, cloud computing and the Internet of
Things (IoT) heralds a new era of hyper connectivity, and with it,
high expectations from students, staff and faculty for anywhere,
anytime Internet availability and data sharing in real time.
Moving services to the cloud can deliver significant infrastructure
benefits and cost efficiencies to help the education sector meet these
new expectations, but these opportunities come with risks that are
sometimes overlooked in the rush to join the crowd in the cloud.
It’s important to consider the risks, as well as the benefits, when
making decisions around out-sourcing IT services to the cloud.
Rethinking business continuity and disaster recovery plans is vital for
ensuring that any investment in cloud services will meet the service
delivery expectation goals of institutions, now and into the future.
This document discusses business intelligence in the cloud. It begins by introducing constraints to traditional BI adoption like costly and inflexible integrated infrastructures. Cloud computing provides an environment for BI that is elastic, low-cost, and flexible. The document then discusses how cloud BI can accelerate adoption, enable easier evaluation and short-term analysis, and increase flexibility. Overall, cloud BI makes BI implementation cheaper and faster while increasing an organization's analytic capabilities.
Harbor Research - Smart Services, Product Analytics, & IntelligenceHarbor Research
Product analytics tools that leverage data from connected products are enabling new capabilities for IT equipment manufacturers and opening up strategic opportunities. Early adopters have seen significant impacts, including double-digit revenue growth, 5-1% increases in return on sales for business units, and service productivity improvements of 20-35%. As product analytics evolves, it will create a "digital nervous system" through connected products that automates most functions and processes, allowing equipment manufacturers to achieve unprecedented customer intimacy and insight.
Dealing with Semantic Heterogeneity in Real-Time InformationEdward Curry
The document discusses computational paradigms for large scale open environments. It describes how environments have shifted from small controlled ones to large open ones with thousands of data sources and schemas. This requires processing information as it flows in real-time from multiple distributed sources. The talk introduces the concept of Information Flow Processing, which processes information as it streams in without intermediate storage. Examples of domains where this paradigm can be applied are given like financial analytics, inventory management and environmental monitoring.
Transforming the Public Sector Affordably in the CloudCapgemini
Case management, provided “as a Service,” is the answer to many current challenges for the public sector.
Political, economic and societal changes mean that public sector organizations must become extremely agile, effective and efficient. This necessitates a new level of flexible,
responsive IT capabilities. Advanced case management, delivered as a managed service, overcomes today’s resource constraints to put these capabilities within reach.
Whether a project lasts two weeks or spans months, no matter if the team consists of three
members or dozens, an electronic document management system can help entities keep track
of the documents, reports, and correspondences involved from the planning to execution phases.
EDM software can help ensure that no project member misses out on key information.
Learn more at the http://na.sage.com/sage-construction-and-real-estate
The document discusses how big data and machine learning are contributing to rapid changes in the world. It provides examples of how industries like lending, education, insurance, and retail have been disrupted by new business models enabled by technologies like mobile, social media, cloud computing, and the internet of things. The rise of startups exploiting big data through applications of machine learning like recommendation engines, image recognition, and autonomous vehicles is also covered. Finally, the document presents an approach for enterprises to harvest big data through a data platform that enables descriptive, advanced, and streaming analytics.
Traditionally, data integration has meant compromise. No matter how rapidly data architects and developers could complete a project before its deadline, speed would always come at the expense of quality. On the other hand, if they focused on delivering a quality project, it would generally drag on for months thus exceeding its deadline. Finally, if the teams concentrated on both quality and rapid delivery, the costs would invariably exceed the budget. Regardless of which path you chose, the end result would be less than desirable. This led some experts to revisit the scope of data integration. This write up shall focus on the same issue.
Slides van Sampo Kellomäki (CTO Synergetics). Datagebruik via Trustplatform en Privacy by Design.
Gepresenteerd tijdens Privacy, Identity & Security (PIDS) seminar van Almere DataCapital, zie www.almeredatacapital.nl.
Full Paper: Analytics: Key to go from generating big data to deriving busines...Piyush Malik
This document discusses how analytics can help organizations derive business value from big data. It describes how statistical analysis, machine learning, optimization and text mining can extract meaningful insights from social media, online commerce, telecommunications, smart utility meters, and improve security. While tools exist to analyze big data, challenges remain around data security, privacy, and developing skilled talent. The paper aims to illustrate how existing algorithms can generate value from different industry use cases.
OpenText PowerDOCS: A Cloud Solution for Document GenerationMarc St-Pierre
OpenText offers a comprehensive cloud solution that functions as a single source for document generation across all use cases, channels, technology platforms, and business systems.
Overlooked aspects of data governance: workflow framework for enterprise data...Anastasija Nikiforova
This presentation is a supplementary material for the article "Overlooked aspects of data governance: workflow framework for enterprise data deduplication" (Azeroual, Nikiforova, Shei) presented at The International Conference on Intelligent Computing, Communication, Networking and Services (ICCNS2023).
Abstract of the paper: Data quality in companies is decisive and critical to the benefits their products and services can provide. However, in heterogeneous IT infrastructures where, e.g., different applications for Enterprise Resource Planning (ERP), Customer Relationship Management (CRM), product management, manufacturing, and marketing are used, duplicates, e.g., multiple entries for the same customer or product in a database or information system, occur. There can be several reasons for this, but the result of non-unique or duplicate records is a degraded data quality. This ultimately leads to poorer, inefficient, and inaccurate data-driven decisions. For this reason, in this paper, we develop a conceptual data governance framework for effective and efficient management of duplicate data, and improvement of data accuracy and consistency in large data ecosystems. We present methods and recommendations for companies to deal with duplicate data in a meaningful way.
Wikipedia (DBpedia): Crowdsourced Data CurationEdward Curry
Wikipedia is an open-source encyclopedia, built collaboratively by a large community of web editors. The success of Wikipedia as one of the most important sources of information available today still challenges existing models of content creation. Despite the fact that the term ‘curation’ is not commonly addressed by Wikipedia’s contributors, the task of digital curation is the central activity of Wikipedia editors, who have the responsibility for information quality standards.
Wikipedia, is already widely used as a collaborative environment inside organizations5.
The investigation of the collaboration dynamics behind Wikipedia highlights important features and good practices which can be applied to different organizations. Our analysis focuses on the curation perspective and covers two important dimensions: social organization and artifacts, tools & processes for cooperative work coordination. These are key enablers that support the creation of high quality information products in Wikipedia’s decentralized environment.
Wolters Kluwer and Risk.Net present the current challenges, priorities and trends influencing banks’ investment in risktech and assesses how they can drive better value in the future. Survey report.
This document proposes a new framework called Actionable Knowledge As A Service (AKAAS) for managing knowledge in cloud computing environments. It discusses how traditional knowledge management systems are challenged by cloud computing and social/technological changes. The framework aims to provide on-demand, customizable knowledge to users based on their needs and interactions. It argues that user behaviors and needs should be the focus, rather than just the volume of published content. Analytics using data on user interactions are proposed to help discover knowledge tailored to specific contexts. The goal is to evolve from push-based knowledge delivery to personalized, actionable knowledge acquisition.
An Environmental Chargeback for Data Center and Cloud Computing ConsumersEdward Curry
Government, business, and the general public increasingly agree that the polluter should pay. Carbon dioxide and environmental damage are considered viable chargeable commodities. The net effect of this for data center and cloud computing operators is that they should look to “chargeback” the environmental impacts of their services to the consuming end-users. An environmental chargeback model can have a positive effect on environmental impacts by linking consumers to the indirect impacts of their usage, facilitating clearer understanding of the impact of their actions. In this paper we motivate the need for environmental chargeback mechanisms. The environmental chargeback model is described including requirements, methodology for definition, and environmental impact allocation strategies. The paper details a proof-of-concept within an operational data center together with discussion on experiences gained and future research directions.
Curry, E.; Hasan, S.; White, M.; and Melvin, H. 2012. An Environmental Chargeback for Data Center and Cloud Computing Consumers. In Huusko, J.; de Meer, H.; Klingert, S.; and Somov, A., eds., First International Workshop on Energy-Efficient Data Centers. Madrid, Spain: Springer Berlin / Heidelberg.
Ericsson Review: Data without borders: an information architecture for enterp...Ericsson
Today’s information systems rely on mediation to use and share the data that is available within an enterprise. But this is changing. IT systems are moving away from traditional architectures, where information is hidden inside functions, toward an information-centric approach that separates information from functionality – data without borders. Breaking functionality and information apart creates a systems architecture that is flexible, supports business agility, and ultimately boosts the bottom line.
Master data management (MDM) is defined as an application-independent process which describes, owns and manages core business data entities. The establishment of the MDM process is a Business Engineering (BE) tasks which requires organizational design. This paper reports on the results of a questionnaire survey among large enterprises aiming at delivering insight into what tasks and master data classes MDM organizations cover (“scope”) and how many people they employ (“size”). The nature of the study is descriptive, i.e. it allows for the identification of patterns and trends in organizing the MDM process.
Richard (Dick) Fisher
Organizations are creating data records at a pace few could have imagined just five years ago - terabytes (1 trillion bytes) now and heading toward petabytes (1,000 terabytes) that may need to be archived or disposed of! This session uses the requirement for archiving and disposition of PeopleSoft records and data elements as one example, plus other real world requirements.
Read more: http://www.rimeducation.com/videos/rimondemand.php
Challenges Ahead for Converging Financial DataEdward Curry
Consumers of financial information come in many guises from personal investors looking for that value for money share, to government regulators investigating corporate fraud, to business executives seeking competitive advantage over their competition. While the particular analysis performed by each of these information consumers will vary, they all have to deal with the explosion of information available from multiple sources including, SEC filings, corporate press releases, market press coverage, and expert commentary. Recent economic events have begun to bring sharp focus on the activities and actions of financial markets, institutions and not least regulatory authorities. Calls for enhanced scrutiny will bring increased regulation and information transparency While extracting information from individual filings is relatively easy to perform when a machine readable format is utilized (for example, using XBRL, the eXtensible Business Reporting Language), cross comparison of extracted financial information can be problematic as descriptions and accounting terms vary across companies and jurisdictions. Across multiple sources the problem becomes the classical data integration problem where a common data abstraction is necessary before functional data use can begin. Within this paper we discuss the challenges in converging financial data from multiple sources. We concentrate on integrating data from multiple sources in terms of the abstraction, linking, and consolidation activities needed to consolidate data before more sophisticated analysis algorithms can examine the data for the objectives of particular information consumers (for e.g. competitive analysis, regulatory compliance, or investor analysis). We base our discussion on several years researching and deploying data integration systems in both the web and enterprise environments.
E. Curry, A. Harth, and S. O’Riain, “Challenges Ahead for Converging Financial Data,” in Proceedings of the XBRL/W3C Workshop on Improving Access to Financial Data on the Web, 2009.
How to mitigate risk in the age of the cloudJames Sankar
The convergence of mobile, cloud computing and the Internet of
Things (IoT) heralds a new era of hyper connectivity, and with it,
high expectations from students, staff and faculty for anywhere,
anytime Internet availability and data sharing in real time.
Moving services to the cloud can deliver significant infrastructure
benefits and cost efficiencies to help the education sector meet these
new expectations, but these opportunities come with risks that are
sometimes overlooked in the rush to join the crowd in the cloud.
It’s important to consider the risks, as well as the benefits, when
making decisions around out-sourcing IT services to the cloud.
Rethinking business continuity and disaster recovery plans is vital for
ensuring that any investment in cloud services will meet the service
delivery expectation goals of institutions, now and into the future.
This document discusses business intelligence in the cloud. It begins by introducing constraints to traditional BI adoption like costly and inflexible integrated infrastructures. Cloud computing provides an environment for BI that is elastic, low-cost, and flexible. The document then discusses how cloud BI can accelerate adoption, enable easier evaluation and short-term analysis, and increase flexibility. Overall, cloud BI makes BI implementation cheaper and faster while increasing an organization's analytic capabilities.
Harbor Research - Smart Services, Product Analytics, & IntelligenceHarbor Research
Product analytics tools that leverage data from connected products are enabling new capabilities for IT equipment manufacturers and opening up strategic opportunities. Early adopters have seen significant impacts, including double-digit revenue growth, 5-1% increases in return on sales for business units, and service productivity improvements of 20-35%. As product analytics evolves, it will create a "digital nervous system" through connected products that automates most functions and processes, allowing equipment manufacturers to achieve unprecedented customer intimacy and insight.
Dealing with Semantic Heterogeneity in Real-Time InformationEdward Curry
The document discusses computational paradigms for large scale open environments. It describes how environments have shifted from small controlled ones to large open ones with thousands of data sources and schemas. This requires processing information as it flows in real-time from multiple distributed sources. The talk introduces the concept of Information Flow Processing, which processes information as it streams in without intermediate storage. Examples of domains where this paradigm can be applied are given like financial analytics, inventory management and environmental monitoring.
Transforming the Public Sector Affordably in the CloudCapgemini
Case management, provided “as a Service,” is the answer to many current challenges for the public sector.
Political, economic and societal changes mean that public sector organizations must become extremely agile, effective and efficient. This necessitates a new level of flexible,
responsive IT capabilities. Advanced case management, delivered as a managed service, overcomes today’s resource constraints to put these capabilities within reach.
Whether a project lasts two weeks or spans months, no matter if the team consists of three
members or dozens, an electronic document management system can help entities keep track
of the documents, reports, and correspondences involved from the planning to execution phases.
EDM software can help ensure that no project member misses out on key information.
Learn more at the http://na.sage.com/sage-construction-and-real-estate
The document discusses how big data and machine learning are contributing to rapid changes in the world. It provides examples of how industries like lending, education, insurance, and retail have been disrupted by new business models enabled by technologies like mobile, social media, cloud computing, and the internet of things. The rise of startups exploiting big data through applications of machine learning like recommendation engines, image recognition, and autonomous vehicles is also covered. Finally, the document presents an approach for enterprises to harvest big data through a data platform that enables descriptive, advanced, and streaming analytics.
Traditionally, data integration has meant compromise. No matter how rapidly data architects and developers could complete a project before its deadline, speed would always come at the expense of quality. On the other hand, if they focused on delivering a quality project, it would generally drag on for months thus exceeding its deadline. Finally, if the teams concentrated on both quality and rapid delivery, the costs would invariably exceed the budget. Regardless of which path you chose, the end result would be less than desirable. This led some experts to revisit the scope of data integration. This write up shall focus on the same issue.
Slides van Sampo Kellomäki (CTO Synergetics). Datagebruik via Trustplatform en Privacy by Design.
Gepresenteerd tijdens Privacy, Identity & Security (PIDS) seminar van Almere DataCapital, zie www.almeredatacapital.nl.
Full Paper: Analytics: Key to go from generating big data to deriving busines...Piyush Malik
This document discusses how analytics can help organizations derive business value from big data. It describes how statistical analysis, machine learning, optimization and text mining can extract meaningful insights from social media, online commerce, telecommunications, smart utility meters, and improve security. While tools exist to analyze big data, challenges remain around data security, privacy, and developing skilled talent. The paper aims to illustrate how existing algorithms can generate value from different industry use cases.
OpenText PowerDOCS: A Cloud Solution for Document GenerationMarc St-Pierre
OpenText offers a comprehensive cloud solution that functions as a single source for document generation across all use cases, channels, technology platforms, and business systems.
Overlooked aspects of data governance: workflow framework for enterprise data...Anastasija Nikiforova
This presentation is a supplementary material for the article "Overlooked aspects of data governance: workflow framework for enterprise data deduplication" (Azeroual, Nikiforova, Shei) presented at The International Conference on Intelligent Computing, Communication, Networking and Services (ICCNS2023).
Abstract of the paper: Data quality in companies is decisive and critical to the benefits their products and services can provide. However, in heterogeneous IT infrastructures where, e.g., different applications for Enterprise Resource Planning (ERP), Customer Relationship Management (CRM), product management, manufacturing, and marketing are used, duplicates, e.g., multiple entries for the same customer or product in a database or information system, occur. There can be several reasons for this, but the result of non-unique or duplicate records is a degraded data quality. This ultimately leads to poorer, inefficient, and inaccurate data-driven decisions. For this reason, in this paper, we develop a conceptual data governance framework for effective and efficient management of duplicate data, and improvement of data accuracy and consistency in large data ecosystems. We present methods and recommendations for companies to deal with duplicate data in a meaningful way.
Enterprises are faced by information overload. Big data appears as an opportunity, but has no relevance until enterprises can put it in context of their activities, processes, and organizations, Applying MDM principles to Big Data is therefore an opportunity that enterprises should target.
This presentation covers the following topics :
- what is MDM and Information Management
- what is Big Data and what are the use cases
- why and how Big Data can take advantage of MDM ? why and how MDM can take advantage of Big Data ?
Using Ontology to Capture Supply Chain Code HalosCognizant
Manufacturers need to create a lingua franca that extends throughout the supply chain ecosystem, in order to generate insights from the digital data encircling their employees, partners, processes and customers.
EDF2013: Invited Talk Julie Marguerite: Big data: a new world of opportunitie...European Data Forum
The document discusses big data opportunities for software services. It summarizes the challenges of handling large amounts of data and extracting useful information through analytics. Key technical challenges include improving data capture, storage, analysis, visualization and developing skills in data science. The document also outlines potential impacts of big data across business domains like cyber security, spatial applications, video surveillance and smart cities.
This document discusses data warehousing and data mining. It defines data warehousing as the process of centralizing data from different sources for analysis. Data mining is described as the process of analyzing data to uncover hidden patterns and relationships. The document provides examples of how data mining and data warehousing can be used together, with data warehousing collecting and organizing data that is then analyzed using data mining techniques to generate useful insights. Applications of data mining and data warehousing discussed include medicine, finance, marketing, and scientific discovery.
Activity Streaming as Information X-DockingKai Riemer
The document discusses activity streaming, which integrates information from various sources into a single stream in real-time. It draws an analogy between activity streaming and cross-docking in logistics. While cross-docking consolidates item flows and facilitates distribution, activity streaming faces challenges in determining information needs, tagging and filtering data from diverse sources, and integrating streams with user environments and roles. Six key challenges of activity streaming are identified: determining information needs, tagging data with metadata, filtering contextual delivery, heterogeneous receivers and senders, and integration with user work practices.
How do social technologies change knowledge worker business processes km me...Martin Sumner-Smith
This document discusses how social technologies may change the business processes of knowledge workers. It begins by defining knowledge workers and noting that while knowledge work depends on social interactions, the best way to support knowledge work with technology is unclear. New social networking approaches may provide useful ways to support knowledge workers. The document then discusses how enterprise content management (ECM) solutions have traditionally addressed unstructured data and processes as well as knowledge management. ECM now encompasses previously separate technologies and everything that can be digitized will eventually become digital. The document examines different dimensions involved in ECM including processes, content, people, and information spectrum. It analyzes how integrating ECM with business processes can increase efficiency and benefits. The key roles of knowledge makers
The document proposes a domain-driven data mining methodology to efficiently process tickets in an IT organization. The methodology involves classifying tickets by category, identifying tickets with high issue rates, applying root cause analysis (RCA) to determine the root cause of issues, and applying continuous improvement (CI) to identify and implement solutions. An experiment applying the methodology to a banking sector showed it improved processing rates and reduced tickets with issues compared to processing tickets independently without categorization or RCA/CI. The methodology aims to efficiently solve ticket issues, increase customer satisfaction and requests, and improve processing without waiting for service level agreements.
Introduction to Data Analytics and data analytics life cycleDr. Radhey Shyam
The document provides an overview of data analytics and big data concepts. It discusses the characteristics of big data, including the four V's of volume, velocity, variety and veracity. It also describes different types of data like structured, semi-structured and unstructured data. The document then introduces big data platforms and tools like Hadoop, Spark and Cassandra. Finally, it discusses the need for data analytics in business, including enabling better decision making and improving efficiency.
“Recognizing Value from a Shared RM/DM Repository: Canadian Government Perspe...Cheryl McKinnon
2003 ARMA Conference Proceedings paper outlining Canadian government examples in content and information management. A historical piece, with focus on Canadian Federal RDIMS initiative up to 2003 and City of Coquitlam. Background to ARMA session co-delivered by Cheryl McKinnon and Heather Gordon
Electronics health records and business analytics a cloud based approachIAEME Publication
This document discusses using business analytics and cloud computing to analyze electronic health records (EHRs). It proposes using pattern recognition algorithms within an intelligent agent on the cloud to better utilize resources and optimize the time needed to analyze EHR requests. The rest of the document outlines related work involving EHR and cloud environments, business scopes and trends related to EHR investments, and a proposed architectural model.
Intelligent Document Management in businesses and e-AdministrationYerbabuena Software
Some 60% of organizations that decide to implement a document management or ECM platform system do so mostly to find a solution to the chaos of information management, more than for any other important reason, such as cost reduction.
This is because, these days, the information overload that exists inside organizations is one of the gravest problems detected in the information society. The excess of information coming into an entity, as a consequence of the massive increase in sources of information (among other aspects) causes the growth of the volume of information to be well above the development capacity that the human resources of any organization can usually count on.
Athento is an ECM solution which is built starting from experience gained from classical management, and which adds a fundamental factor for success: a system of intelligent management.
The rise of the digital supply network - IIOT Industry40 distribution Ian Beckett
The document discusses the rise of digital supply networks (DSNs) enabled by Industry 4.0 technologies. Key points include:
- Industry 4.0 technologies like IoT, analytics, automation and 3D printing are enabling the transformation of traditional linear supply chains into interconnected DSNs.
- DSNs integrate information from many sources in real-time to provide end-to-end transparency, intelligent optimization, and holistic decision making across the supply network.
- Characteristics like always-on agility and a connected community allow DSNs to minimize latency and inefficiencies compared to traditional supply chains.
This document summarizes a survey on data mining. It discusses how data mining helps extract useful business information from large databases and build predictive models. Commonly used data mining techniques are discussed, including artificial neural networks, decision trees, genetic algorithms, and nearest neighbor methods. An ideal data mining architecture is proposed that fully integrates data mining tools with a data warehouse and OLAP server. Examples of profitable data mining applications are provided in industries such as pharmaceuticals, credit cards, transportation, and consumer goods. The document concludes that while data mining is still developing, it has wide applications across domains to leverage knowledge in data warehouses and improve customer relationships.
Data Wrangling for Big Data Challenges andOpportunities.docxwhittemorelucilla
This document discusses the challenges and opportunities of data wrangling for big data. It argues that providing cost-effective, highly-automated approaches to data wrangling involves significant research challenges. Specifically, it discusses the need to make well-informed compromises by capturing user requirements, to extend data boundaries by leveraging external sources, to make use of all available contextual information, and to adopt an incremental pay-as-you-go approach that allows for flexible user feedback. Addressing these challenges will require fundamental changes to established data extraction, integration and cleaning techniques.
Data Mining in Telecommunication Industryijsrd.com
Telecommunication companies today are operating in highly competitive and challenging environment. Vast volume of data is generated from various operational systems and these are used for solving many business problems that required urgent handling. These data include call detail data, customer data and network data. Data Mining methods and business intelligence technology are widely used for handling the business problems in this industry. The goal of this paper is to provide a broad review of data mining concepts.
Big data refers to extremely large data sets that traditional data processing systems cannot handle. Big data is characterized by high volume, velocity, and variety of data. Hadoop is an open-source software framework that allows distributed storage and processing of big data across clusters of computers. A key component of Hadoop is MapReduce, a programming model that enables parallel processing of large datasets. MapReduce allows programmers to break problems into independent pieces that can be processed simultaneously across distributed systems.
Knowledge management (KM) has become an effective way of managing organization‟s intellectual capital or, in other words, organization‟s full experience, skills and knowledge that is relevant for more effective performance in future. The paper proposes a knowledge management to achieve a competitive control of the machining systems. Then an application of Knowledge Management in engineering has been attempted to explain. The model can be used by the manager for the choosing of competitive orders.
Information Governance, Managing Data To Lower Risk and Costs, and E-Discover...David Kearney
Information governance, records and information management, and data disposition policies are ways to help lower costs and mitigate risks for organizations. Policies and procedures to actively manage data are not just an IT "problem," they're a collaborative business initiative that is a must in today's "big data" environment. With electronic discovery rules, government regulations and the Sarbanes-Oxley Act, all organizations must proactively take steps to manage their data with well-governed processes and controls, or be willing to face the risks and costs that come along with keeping everything. Organizations must know what information they have, where it is located, the duration data must be retained and what information would be needed when responding to an event.
There have been numerous instances of severe legal penalties for organizations that did not have an electronic data strategy, tools, processes and controls to locate and understand their own data. In addition, the risks of unmanaged data include skyrocketing infrastructure and personnel costs and an increase in attorney time to manage massive amounts of data when a litigation event occurs.
Information governance is needed much like any business continuity and disaster recovery plans, but with an understanding of data: where data are located, how data are managed, event response, and regular testing of processes and procedures for preparedness.
Information Governance, Managing Data To Lower Risk and Costs, and E-Discover...
Jahima Edrm Imrm
1. Working Smart a professional practice forum
ARRA on the Job / e-HIM Best Practices / Data Standards / Legal e-Speaking
Easing e-Discovery
The Electronic Discovery Reference Model and the Information Management
Reference Model
By William S. Horn, MBA
T
The elecTronic Discovery reference Model (eDrM) vendors were able to map their products and services to steps in
project offers guidelines and standards for e-discovery. it has the process and to use industry-defined terms to describe their
helped reduce the cost, time, and manual work associated with offerings for customer comparison.
e-discovery and has proven to be invaluable to those engaged in The sidebar offers a high-level description of the model.
litigation support since its creation in 2005. The eDrM has been enormously successful in defining the e-
now this model is traveling upstream in order to provide the discovery process not only for vendors and customers, but also
same benefits to records and information management profes- for the courts and regulators. The group’s standards have led to
sionals. in particular, a subgroup is dedicated to providing a additional guidelines by the sedona conference and changes to
healthcare-specific viewpoint in the information Management the Federal rules of civil Procedure governing the interaction
reference Model. between parties in federal court proceedings.
EDRM—A Common Framework IMRM—Moving Upstream
in order to understand the growth and impact of electronically Technology improvements have made it easier to find informa-
stored information, imagine the following scenario. A hospital tion. however, they have also highlighted some problems:
receives a request from a federal court for all information relat- xx x atax storagex isx growingx unchecked.x Organizationsx arex
D
ed to patients who are potentially part of a class action lawsuit creatingxmorexdata,xbutxe-discoveryxhasxrevealedxthatxtoox
involving a regulated drug or medical device. The court requests manyx arex notx managingx itx throughx thex entirex lifecyclex tox
electronic health records, all medical images, e-mail communi- disposition.x Thisx excessivex volumex increasesx thex riskx ofx
cations, medical bills, and any other type of electronic informa- findingxdamagingxinformationxandxe-discoveryxcosts.
tion for dozens of patients over several years. xx x txisxtooxhardxtoxfindxallxrelevantxdata.xDepartmentsxsome-
I
requests such as these led to an influx of vendors with tech- timesxoperatexindependently,xandxlegalxteamsxunfamiliarx
nology products and services designed to quickly find and pre- withx thex businessx operationsx andx informationx manage-
pare relevant information for presentation to a court or regu- mentx lackx ax comprehensivex viewx ofx wherex thex datax theyx
lator. Unfortunately, customers evaluating different vendors needxarexstored.
found it challenging to make an “apples to apples” comparison. xx x Txdepartmentsxdoxnotxhavexcontrolxoverxcopiesxofxdocu-
I
vendors too found it frustrating to differentiate themselves from ments.xItxisxnotxenoughxtoxdestroyxanxoriginalxdocumentxorx
others in the marketplace. e-mailxatxthexendxofxitsxlifecycle.xCopiesxarexstillxdiscover-
litigation attorneys George socha and Tom Gelbmann con- ablexandxposexthexsamexrisksxandxcosts.xInxfactxitxisxworsex
firmed these issues with an industry survey and subsequently ifxlegalxcounselxreportsxtoxthexcourtsxorxregulatorsxthatxthex
founded the eDrM project to define the e-discovery process in dataxdoxnotxexistxonlyxtoxfindxaxcopyxlater.
a simple model with common terminology. Through this model, xx x rganizationsxlackxaxcomprehensivexrecordsxholdxprocess.x
O
44 / Journal of AHIMA January 10
3. Working Smart a professional practice forum
ARRA on the Job / e-HIM Best Practices / Data Standards / Legal e-Speaking
panies, service providers, and corporations in several industries The iMrM will be published in draft form for comment in ear-
who came to the table with business, legal, and iT backgrounds. ly 2010 at www.eDrM.net. it will include a high-level diagram
The healthcare industry stood out as unique as participants and glossary describing the types of information systems, roles
discussed their experiences in information management. ev- of key stakeholders, and the relationships between them. it will
eryone had heard the healthcare reform discussions stressing also include a detailed maturity model for benchmarking.
the need for a migration to electronic health records manage- The model will describe four levels of information manage-
ment. Most had worked in industries that had been automated ment maturity with regard to the distinct stages of the infor-
and electronically integrated with business partners for years, if mation lifecycle, the recognition of roles and responsibilities
not decades. stated in policies and procedures, the rate of adoption among
Members were aware of digital automation in pharmaceutical the workforce, the level of integration between stakeholders’
and insurance companies and knew that larger hospitals gener- systems, the governance structure of the information program,
ally had system applications, but the degree of penetration in and the monitoring capabilities for continuous improvement.
the provider community and the integration between business it will also have a risk assessment component so that organi-
partners seemed to be lacking. it struck the group that if it could zations can measure gaps based on current state and desired
build an iMrM specifically for healthcare, the industry may be levels of maturity and weight those gaps according to impact of
able to avoid some of the mistakes made by other industries as noncompliance, likelihood of occurrence, alignment with stra-
they automated. tegic priorities, cultural fit, and ease of implementation.
A better understanding of the e-discovery process and re-
cords and information management fundamentals will help
healthcare organizations reduce legal and regulatory risk as
well as reduce e-discovery review costs. A more comprehensive
understanding of the information flow will lead to operational
efficiencies through end-to-end business process improve-
ments. A common understanding of departmental information
requirements and a common terminology to describe them can
improve purchasing decisions, reducing costs through shared
iT applications and better systems integration. These are just a
few of the potential benefits of the healthcare iMrM, but clearly
it will be an asset as the industry moves to electronic health re-
cords.
The iMrM will change over time just as the eDrM matured
over a few years and continues to evolve. Developing and im-
plementing the iMrM will not be trivial. however, information
management professionals in the healthcare industry are well
suited to the challenge.
The iMrM project welcomes participants. More information
may be found at www.eDrM.net. ¢
Note
1. “information Management reference Model.” Available
online at http://edrm.net/activities/projects/information-
management-reference-model.
William S. Horn (william.s.horn@comcast.net) is a management consultant
with Cohasset Associates, Inc. and a current member of the EDRM project.
Read More in the Body of Knowledge
Read more about e-discovery in the AHIMA Body of Knowledge at
www.ahima.org. Search on “e-discovery.” In addition, three years of
“Legal e-Speaking” columns offer guidance on HIM practices that
support legally sound business records and describe the emerging
practice of enterprise content and records management.
46 / Journal of AHIMA January 10