Data Center Decisions: Build Versus BuyVISIHOSTING
The document discusses strategies for data center decisions around building versus buying data center capacity. It covers trends in decreasing data center sizes and power needs due to virtualization and server consolidation. It also emphasizes the importance of flexibility in data center design given the fast pace of technological changes. The document advocates evaluating both operational needs and facilities capabilities when establishing a data center strategy.
This document provides an overview of a lecture on the impact of information technology (IT) on management decision making. It discusses how organizations can influence how IT is used through decisions about technical infrastructure and IT services. It also examines the roles of managers in organizations and the different types of decisions they make at strategic, management, and operational levels. Decision-making tools like SWOT analysis and critical success factors are also introduced to help evaluate organizational strengths, weaknesses, opportunities, threats and goals.
The document discusses the evolution of corporate learning ecosystems from traditional formal learning approaches to more connected, collaborative approaches. It notes several trends driving this change, including cognitive overload, generational impacts, and a gap between learning at home and work. The author advocates for a learning ecosystem that allows employees to learn through interactions with peers, experts, and resources. Examples are provided of how this contrasts with traditional learning models and how organizations can transition to support more social, connected learning.
Healthcare Simulation:
Bed Allocation in Hospital:
Simcad Pro is a sophisticated simulation engine that can be utilized to improve the overall efficiency of the Emergency Room. The use of Simcad Pro has been shown to improve Emergency Room efficiency, accuracy and effectiveness, which in turn improves patient outcomes and the quality of care that is received. In addition, staff allocation and efficiency can be better forecasted and analyzed, reducing the overall cost of care without sacrificing the quality of care.
Taking the Training Wheels Off Social SoftwareAlan Lepofsky
The Shift From Sharing To Getting Work Done
Over the last few years employees have slowly grown accustomed to using social software at work. Actions such as posting status updates, sharing links to web sites and publishing personal blogs have provided great starting points for getting people engaged, but now it's time for employees to start using social software to help Get Work Done. In this session we'll discuss the growing trends of using social tools for task/project management and integration of social elements into core-businesses process. You'll hear how departments such as Human Resources, Marketing and Support can use social technologies to improve the way people work. Topics will include social/workforce analytics, social media monitoring, mobile devices and gamification. It's time to take social software from a tool for sharing to a key contributor of company success.
Presented at E2Conf Boston by
Alan Lepofsky and Yvette Cameron of Constellation Research
Presentation given at Enterprise 2.0 Conference 2011 in Santa Clara. Highlights lessons learned from SAP's journey in embedding social media in marketing
First presented at http://www.e2conf.com/virtual/
The value of Social Analytics can be surfaced in many ways. Sometimes is quite visual like a leader board that helps motivate participation. Other times it's behind the scenes like the algorithms used to recommend groups to join or pages to read. Either way, social analytics can help you make better informed decisions, provide more relevancies to your interactions and ultimately help you get you and your company be more successful. This session will take a look at some of the real world implementations of social analytics available today from many of the social business vendors. We'll talk about the trends in this space and discuss some of the possible future directions.
Data Center Decisions: Build Versus BuyVISIHOSTING
The document discusses strategies for data center decisions around building versus buying data center capacity. It covers trends in decreasing data center sizes and power needs due to virtualization and server consolidation. It also emphasizes the importance of flexibility in data center design given the fast pace of technological changes. The document advocates evaluating both operational needs and facilities capabilities when establishing a data center strategy.
This document provides an overview of a lecture on the impact of information technology (IT) on management decision making. It discusses how organizations can influence how IT is used through decisions about technical infrastructure and IT services. It also examines the roles of managers in organizations and the different types of decisions they make at strategic, management, and operational levels. Decision-making tools like SWOT analysis and critical success factors are also introduced to help evaluate organizational strengths, weaknesses, opportunities, threats and goals.
The document discusses the evolution of corporate learning ecosystems from traditional formal learning approaches to more connected, collaborative approaches. It notes several trends driving this change, including cognitive overload, generational impacts, and a gap between learning at home and work. The author advocates for a learning ecosystem that allows employees to learn through interactions with peers, experts, and resources. Examples are provided of how this contrasts with traditional learning models and how organizations can transition to support more social, connected learning.
Healthcare Simulation:
Bed Allocation in Hospital:
Simcad Pro is a sophisticated simulation engine that can be utilized to improve the overall efficiency of the Emergency Room. The use of Simcad Pro has been shown to improve Emergency Room efficiency, accuracy and effectiveness, which in turn improves patient outcomes and the quality of care that is received. In addition, staff allocation and efficiency can be better forecasted and analyzed, reducing the overall cost of care without sacrificing the quality of care.
Taking the Training Wheels Off Social SoftwareAlan Lepofsky
The Shift From Sharing To Getting Work Done
Over the last few years employees have slowly grown accustomed to using social software at work. Actions such as posting status updates, sharing links to web sites and publishing personal blogs have provided great starting points for getting people engaged, but now it's time for employees to start using social software to help Get Work Done. In this session we'll discuss the growing trends of using social tools for task/project management and integration of social elements into core-businesses process. You'll hear how departments such as Human Resources, Marketing and Support can use social technologies to improve the way people work. Topics will include social/workforce analytics, social media monitoring, mobile devices and gamification. It's time to take social software from a tool for sharing to a key contributor of company success.
Presented at E2Conf Boston by
Alan Lepofsky and Yvette Cameron of Constellation Research
Presentation given at Enterprise 2.0 Conference 2011 in Santa Clara. Highlights lessons learned from SAP's journey in embedding social media in marketing
First presented at http://www.e2conf.com/virtual/
The value of Social Analytics can be surfaced in many ways. Sometimes is quite visual like a leader board that helps motivate participation. Other times it's behind the scenes like the algorithms used to recommend groups to join or pages to read. Either way, social analytics can help you make better informed decisions, provide more relevancies to your interactions and ultimately help you get you and your company be more successful. This session will take a look at some of the real world implementations of social analytics available today from many of the social business vendors. We'll talk about the trends in this space and discuss some of the possible future directions.
This document provides an overview of an introductory course on information systems and information technology. It defines key terms like information systems, information technology, data, information, and knowledge. It describes the major functions and capabilities of information systems. It also outlines different types of information systems including transaction processing systems, management information systems, decision support systems, and enterprise-wide systems that support organizational levels and business functions.
This document provides an agenda and summary for a technology and strategy class. It includes the following:
- An agenda covering administrative announcements, IT news, and a discussion on technology and strategy.
- A discussion of concepts like Web 1.0 vs 2.0, what is Web 3.0, and critical questions about how organizations use IT and evaluate new technologies.
- Models for information, technology, and the systems development life cycle.
BigML's take on Big Data. University of Geneva, October 12, 2012.
In the "Big Data" era, rapidly and easily getting insights from your data or creating data-driven applications does not have to be painful. BigML shows how business managers, application developers, and data scientists can start building their own predictive models in a matter of minutes.
This document discusses IT governance in small and medium enterprises (SMEs). It explores whether IT governance in SMEs is based more on control or trust when outsourcing IT projects. The document outlines definitions of SMEs, issues they face with IT and outsourcing, and introduces the concepts of agency theory and organizational trust as theoretical frameworks. It then describes the research methodology used - a retrospective multiple case study analysis of SMEs that experienced outsourced IT project failures. The document puts forward four propositions relating project failure to levels of control and trust.
An outline of knowledge mining multi tier architecture for decision makingIAEME Publication
1. The document proposes a multi-tier architecture for a knowledge mining tool to support decision making.
2. It describes key aspects of decision making processes, knowledge management systems, and existing approaches to knowledge discovery in databases.
3. The proposed architecture is a three-tier system with graphical interface, client-side services, and centralized middle-tier services that control mining tasks and access data sources to produce results for users.
The document provides an overview of key concepts related to information systems, including:
- Data vs. information, inputs, processing, outputs, and feedback in information systems.
- Characteristics of systems like inputs, processes, outputs, feedback, and how systems can be modeled.
- The five basic parts of a computer-based information system: hardware, software, databases, telecommunications, and networks.
Design for Interaction
by Daniel Tunkelang, Chief Scientist of Endeca
An invited presentation at SIGMOD '09 (http://sigmod09.org/)
Research in information retrieval has focused on presenting the most relevant results to a user in response to a free-text search query. Research in database systems assumes a model where the user enters a formal query, and the results are exactly those the user requested. Neither community has emphasized user interaction—a critical concern for practical information access.
As William Goffman noted in the 1960s and Nick Belkin continually reminds us today, the relationship between a document and query, though necessary, is not sufficient to determine relevance—yet ranked retrieval approaches rely heavily or exclusively on this relationship. Meanwhile, recent work on database usability by Jeff Naughton and H.V. Jagadish surfaces the rigidity of database systems that return nothing unless users know how to formulate precise queries.
This talk presents human-computer information retrieval (HCIR) as a general approach that addresses some of the key challenges facing both research communities. A vision first put forward by Gary Marchionini, HCIR expects people and systems to work together to implement information access. Such an approach requires rethinking information access not as a matching or ranking problem, but rather as a communication problem. Specifically, we need interfaces that optimize the bidirectional communication between the user and the system, thus optimizing the symbiotic division of labor between the two.
This talk reviews the history of HCIR efforts and presents ongoing work to implement the HCIR vision. In particular, it presents an interactive set retrieval approach that responds to queries with an overview of the user's current context and an organized set of options for incremental exploration.
Taming Big Science Data Growth with Converged InfrastructureThe BioTeam Inc.
2014 BioIT World Expo presentation
"Many of the largest NGS sites have identified IO bottlenecks as their number one concern in growing their infrastructure to support current and projected data growth rates. In this talk Aaron D. Gardner, Senior Scientific Consultant, BioTeam, Inc. will share real-world strategies and implementation details for building converged storage infrastructure to support the performance, scalability and collaborative requirements of today's NGS workflows. "
For a copy of this presentation please email: chris@bioteam.net
Wragge & Co Mobile Healthcare Industry Summit 2012 Bleddyn Rees3GDR
The document discusses creating permanent mobile health ecosystems. It describes the European Connected Health Alliance as promoting the widespread adoption of connected health devices and services. The Alliance sets up ecosystems to deploy connected health solutions across regions by transferring best practices. Barriers to adoption include complexity, interoperability issues, lack of evidence, and regulatory concerns. The Alliance's ecosystems aim to address these barriers by developing networks focused on integrating healthcare as an investment. Successful business models include managed service models where providers supply services rather than just equipment. The conclusion emphasizes the need for a supportive legal framework and better public education on connected health.
Themes and objectives:
To position FAIR as a key enabler to automate and accelerate R&D process workflows
FAIR Implementation within the context of a use case
Grounded in precise outcomes (e.g. faster and bigger science / more reuse of data to enhance value / increased ability to share data for collaboration and partnership)
To make data actionable through FAIR interoperability
Speakers:
Mathew Woodwark,Head of Data Infrastructure and Tools, Data Science & AI, AstraZeneca
Erik Schultes, International Science Coordinator, GO-FAIR
Georges Heiter, Founder & CEO, Databiology
Intel Social Computing & Sustainability IssuesUmair Mohsin
Intel IT's social computing initiative aims to improve knowledge sharing and collaboration among employees. Key aspects include establishing a suite of social tools for finding experts, sharing ideas, and enriching communications. The goals are to break down information silos, engage younger employees, and mitigate the impact of a maturing workforce. Intel IT is also focusing on the highest impact sustainability opportunities like data center optimization and energy efficient PCs to reduce resource consumption and waste.
New Perspectives for Business Intelligence: Library and Research Technologies...Robert H. McDonald
This is our presentation for Educause 2012 entitled New Perspectives for Business Intelligence: Library and Research Technologies and Research Collaboration for New Data Models held on Nov 8, 2012.
Managing 'Big Data': Federal use cases for real-time data infrastructureSchneider Electric
OSIsoft's PI System - a software data infrastructure for real-time and event data is a necessary underpinning for monitoring, measurement, and incremental improvement in complex critical infrastructure environments. Hear about use cases and return on investment relevant to federal projects where energy management, operations optimization, and real-time situational awareness are priority goals.
This document discusses knowledge engineering for health and big data. It notes that the rate of data generation is changing but complexity, requirement to use data, and mass of useless data are stable. Knowledge engineering was first defined in 1983 as integrating knowledge into computer systems to solve complex problems. The document discusses building a knowledge engineering community and notes a need for standards around semantics, syntax, technology, and quality. It advocates for a knowledge extraction approach rather than data warehouses and discusses architectural concepts, policy and strategy considerations, and acknowledges GEN2PHEN partners and funding sources.
As Global thought leader on Digitalization of Governments, I was asked to address the Minister of ICT and Senior Government leaders at a conference in Port Louis. My keynote presentation addressed how ICT innovations - especially in LDC's and MDC's can greatly improve eGovernment implementation success - especially if three key prerequicites are remembered: Good Master Data, Good Identification of Citizen and Good Communication Infrastructure. Also outlined a number of recommendations that Governments can follow to be successful with eGovernment Implementations.
Jack Kufahl, Director of the Solutions Center, Medical School Information Services (MSIS) at the University of Michigan, gave this presentation at the seminar "iPhone and iPad in the Health Sciences" on 13 March 2012. In this presentation, Kufahl describes how the Solutions Center provides support for Medical School staff and faculty who are interested in developing mobile apps for use in teaching, research, or administration. His presentation includes examples of several applications currently in use at the University of Michigan Medical School.
David Rose provided an ovevriew of Governance with regards to Enterprise Architecture.
Presented at the first JISC Emerging Practices workshop (2012/03/29).
http://emergingpractices.jiscinvolve.org/wp/doing-ea-workshop/
ISSC340_Presentation_Ronald_Averion.pptxNAME Ronald Averi.docxchristiandean12115
ISSC340_Presentation_Ronald_Averion.pptx
NAME: Ronald Averion
TITLE: SHARED iDRIVE
INTRODUCTION
Efficiency in data storage and data retrieval is a key factor in the productivity of an organization.
iDRIVE enables data to be securely stored, retrieved and shared in an efficient manner.
Background information
Shared drive enhances sharing of data in a networked environment.
Users are divided into user groups so that privileges can be effected and managed easily
For security purposes, users can access specific data depending on their user group.
Conventional storage mechanisms don’t offer this flexibility.
This is an Information Technology Supported, which has been authorized and one that is managed to give space for storage space electronically for the users that has been authorized for some given network. In some cases the drive is given the name as the J: Drive (Phillips & Skagerberg, 2003). The use of the share drive is necessary because it enables information to be store in one place and the users from same department can share it increasing efficiency in an organisation.
2
OBJECTIVES
To carry out research on how old methods of sharing data was done.
To investigate the drawbacks of the old methods of storing data.
To carry out research on how shared drive is implemented.
To show the advantages of using shared drive technology in an organization.
To carry out research on how old method of sharing files was done.
To investigate the drawbacks of the old method of storing files.
To carry out research on how shared drive is implemented.
To recommend use of shared drive in an organization.
3
REQUIREMENTS
The shared drive should conform to Professional and Ethical standards.
Enough funds to facilitate the whole project.
Hardware requirements(computers, servers , internetworking tools)
Software requirements(Windows server2012 R2)
Contribute to society and human well-being.
Does your application infringe on any fundamental human rights?
Avoid harm to others.
Be honest and trustworthy.
4
ADVANTAGES OF IDRIVE
It enables various users in an organization to share information and data
Facilitates easier retrieval of data. This enhances performance and productivity.
Enhances data security by implementing user groups and privileges
Eliminates unnecessary duplication of data(Besanko, 2010). This makes it easier when it comes to sorting out of the files and hence makes it easier to retrieve it.
It enables the various members of a given staff who are working in some work areas to have knowledge of the exact place from which they have the ability of accessing enjoy form of information that they want.
It enables folders to be kept in a hierarchy that can be controlled hence enabling the electronic folders and the tittles of the documents which have been stored hence easing the situation in which some given form of information is required to be retrieved from the system.
The third advantage is that the electronic information which rel.
The following topics are discussed in this presentation
Data and Information
Database
Database Management System
Objectives
Advantages
Components
Architecture
This document provides an overview of an introductory course on information systems and information technology. It defines key terms like information systems, information technology, data, information, and knowledge. It describes the major functions and capabilities of information systems. It also outlines different types of information systems including transaction processing systems, management information systems, decision support systems, and enterprise-wide systems that support organizational levels and business functions.
This document provides an agenda and summary for a technology and strategy class. It includes the following:
- An agenda covering administrative announcements, IT news, and a discussion on technology and strategy.
- A discussion of concepts like Web 1.0 vs 2.0, what is Web 3.0, and critical questions about how organizations use IT and evaluate new technologies.
- Models for information, technology, and the systems development life cycle.
BigML's take on Big Data. University of Geneva, October 12, 2012.
In the "Big Data" era, rapidly and easily getting insights from your data or creating data-driven applications does not have to be painful. BigML shows how business managers, application developers, and data scientists can start building their own predictive models in a matter of minutes.
This document discusses IT governance in small and medium enterprises (SMEs). It explores whether IT governance in SMEs is based more on control or trust when outsourcing IT projects. The document outlines definitions of SMEs, issues they face with IT and outsourcing, and introduces the concepts of agency theory and organizational trust as theoretical frameworks. It then describes the research methodology used - a retrospective multiple case study analysis of SMEs that experienced outsourced IT project failures. The document puts forward four propositions relating project failure to levels of control and trust.
An outline of knowledge mining multi tier architecture for decision makingIAEME Publication
1. The document proposes a multi-tier architecture for a knowledge mining tool to support decision making.
2. It describes key aspects of decision making processes, knowledge management systems, and existing approaches to knowledge discovery in databases.
3. The proposed architecture is a three-tier system with graphical interface, client-side services, and centralized middle-tier services that control mining tasks and access data sources to produce results for users.
The document provides an overview of key concepts related to information systems, including:
- Data vs. information, inputs, processing, outputs, and feedback in information systems.
- Characteristics of systems like inputs, processes, outputs, feedback, and how systems can be modeled.
- The five basic parts of a computer-based information system: hardware, software, databases, telecommunications, and networks.
Design for Interaction
by Daniel Tunkelang, Chief Scientist of Endeca
An invited presentation at SIGMOD '09 (http://sigmod09.org/)
Research in information retrieval has focused on presenting the most relevant results to a user in response to a free-text search query. Research in database systems assumes a model where the user enters a formal query, and the results are exactly those the user requested. Neither community has emphasized user interaction—a critical concern for practical information access.
As William Goffman noted in the 1960s and Nick Belkin continually reminds us today, the relationship between a document and query, though necessary, is not sufficient to determine relevance—yet ranked retrieval approaches rely heavily or exclusively on this relationship. Meanwhile, recent work on database usability by Jeff Naughton and H.V. Jagadish surfaces the rigidity of database systems that return nothing unless users know how to formulate precise queries.
This talk presents human-computer information retrieval (HCIR) as a general approach that addresses some of the key challenges facing both research communities. A vision first put forward by Gary Marchionini, HCIR expects people and systems to work together to implement information access. Such an approach requires rethinking information access not as a matching or ranking problem, but rather as a communication problem. Specifically, we need interfaces that optimize the bidirectional communication between the user and the system, thus optimizing the symbiotic division of labor between the two.
This talk reviews the history of HCIR efforts and presents ongoing work to implement the HCIR vision. In particular, it presents an interactive set retrieval approach that responds to queries with an overview of the user's current context and an organized set of options for incremental exploration.
Taming Big Science Data Growth with Converged InfrastructureThe BioTeam Inc.
2014 BioIT World Expo presentation
"Many of the largest NGS sites have identified IO bottlenecks as their number one concern in growing their infrastructure to support current and projected data growth rates. In this talk Aaron D. Gardner, Senior Scientific Consultant, BioTeam, Inc. will share real-world strategies and implementation details for building converged storage infrastructure to support the performance, scalability and collaborative requirements of today's NGS workflows. "
For a copy of this presentation please email: chris@bioteam.net
Wragge & Co Mobile Healthcare Industry Summit 2012 Bleddyn Rees3GDR
The document discusses creating permanent mobile health ecosystems. It describes the European Connected Health Alliance as promoting the widespread adoption of connected health devices and services. The Alliance sets up ecosystems to deploy connected health solutions across regions by transferring best practices. Barriers to adoption include complexity, interoperability issues, lack of evidence, and regulatory concerns. The Alliance's ecosystems aim to address these barriers by developing networks focused on integrating healthcare as an investment. Successful business models include managed service models where providers supply services rather than just equipment. The conclusion emphasizes the need for a supportive legal framework and better public education on connected health.
Themes and objectives:
To position FAIR as a key enabler to automate and accelerate R&D process workflows
FAIR Implementation within the context of a use case
Grounded in precise outcomes (e.g. faster and bigger science / more reuse of data to enhance value / increased ability to share data for collaboration and partnership)
To make data actionable through FAIR interoperability
Speakers:
Mathew Woodwark,Head of Data Infrastructure and Tools, Data Science & AI, AstraZeneca
Erik Schultes, International Science Coordinator, GO-FAIR
Georges Heiter, Founder & CEO, Databiology
Intel Social Computing & Sustainability IssuesUmair Mohsin
Intel IT's social computing initiative aims to improve knowledge sharing and collaboration among employees. Key aspects include establishing a suite of social tools for finding experts, sharing ideas, and enriching communications. The goals are to break down information silos, engage younger employees, and mitigate the impact of a maturing workforce. Intel IT is also focusing on the highest impact sustainability opportunities like data center optimization and energy efficient PCs to reduce resource consumption and waste.
New Perspectives for Business Intelligence: Library and Research Technologies...Robert H. McDonald
This is our presentation for Educause 2012 entitled New Perspectives for Business Intelligence: Library and Research Technologies and Research Collaboration for New Data Models held on Nov 8, 2012.
Managing 'Big Data': Federal use cases for real-time data infrastructureSchneider Electric
OSIsoft's PI System - a software data infrastructure for real-time and event data is a necessary underpinning for monitoring, measurement, and incremental improvement in complex critical infrastructure environments. Hear about use cases and return on investment relevant to federal projects where energy management, operations optimization, and real-time situational awareness are priority goals.
This document discusses knowledge engineering for health and big data. It notes that the rate of data generation is changing but complexity, requirement to use data, and mass of useless data are stable. Knowledge engineering was first defined in 1983 as integrating knowledge into computer systems to solve complex problems. The document discusses building a knowledge engineering community and notes a need for standards around semantics, syntax, technology, and quality. It advocates for a knowledge extraction approach rather than data warehouses and discusses architectural concepts, policy and strategy considerations, and acknowledges GEN2PHEN partners and funding sources.
As Global thought leader on Digitalization of Governments, I was asked to address the Minister of ICT and Senior Government leaders at a conference in Port Louis. My keynote presentation addressed how ICT innovations - especially in LDC's and MDC's can greatly improve eGovernment implementation success - especially if three key prerequicites are remembered: Good Master Data, Good Identification of Citizen and Good Communication Infrastructure. Also outlined a number of recommendations that Governments can follow to be successful with eGovernment Implementations.
Jack Kufahl, Director of the Solutions Center, Medical School Information Services (MSIS) at the University of Michigan, gave this presentation at the seminar "iPhone and iPad in the Health Sciences" on 13 March 2012. In this presentation, Kufahl describes how the Solutions Center provides support for Medical School staff and faculty who are interested in developing mobile apps for use in teaching, research, or administration. His presentation includes examples of several applications currently in use at the University of Michigan Medical School.
David Rose provided an ovevriew of Governance with regards to Enterprise Architecture.
Presented at the first JISC Emerging Practices workshop (2012/03/29).
http://emergingpractices.jiscinvolve.org/wp/doing-ea-workshop/
ISSC340_Presentation_Ronald_Averion.pptxNAME Ronald Averi.docxchristiandean12115
ISSC340_Presentation_Ronald_Averion.pptx
NAME: Ronald Averion
TITLE: SHARED iDRIVE
INTRODUCTION
Efficiency in data storage and data retrieval is a key factor in the productivity of an organization.
iDRIVE enables data to be securely stored, retrieved and shared in an efficient manner.
Background information
Shared drive enhances sharing of data in a networked environment.
Users are divided into user groups so that privileges can be effected and managed easily
For security purposes, users can access specific data depending on their user group.
Conventional storage mechanisms don’t offer this flexibility.
This is an Information Technology Supported, which has been authorized and one that is managed to give space for storage space electronically for the users that has been authorized for some given network. In some cases the drive is given the name as the J: Drive (Phillips & Skagerberg, 2003). The use of the share drive is necessary because it enables information to be store in one place and the users from same department can share it increasing efficiency in an organisation.
2
OBJECTIVES
To carry out research on how old methods of sharing data was done.
To investigate the drawbacks of the old methods of storing data.
To carry out research on how shared drive is implemented.
To show the advantages of using shared drive technology in an organization.
To carry out research on how old method of sharing files was done.
To investigate the drawbacks of the old method of storing files.
To carry out research on how shared drive is implemented.
To recommend use of shared drive in an organization.
3
REQUIREMENTS
The shared drive should conform to Professional and Ethical standards.
Enough funds to facilitate the whole project.
Hardware requirements(computers, servers , internetworking tools)
Software requirements(Windows server2012 R2)
Contribute to society and human well-being.
Does your application infringe on any fundamental human rights?
Avoid harm to others.
Be honest and trustworthy.
4
ADVANTAGES OF IDRIVE
It enables various users in an organization to share information and data
Facilitates easier retrieval of data. This enhances performance and productivity.
Enhances data security by implementing user groups and privileges
Eliminates unnecessary duplication of data(Besanko, 2010). This makes it easier when it comes to sorting out of the files and hence makes it easier to retrieve it.
It enables the various members of a given staff who are working in some work areas to have knowledge of the exact place from which they have the ability of accessing enjoy form of information that they want.
It enables folders to be kept in a hierarchy that can be controlled hence enabling the electronic folders and the tittles of the documents which have been stored hence easing the situation in which some given form of information is required to be retrieved from the system.
The third advantage is that the electronic information which rel.
The following topics are discussed in this presentation
Data and Information
Database
Database Management System
Objectives
Advantages
Components
Architecture
Data Science: An Emerging Field for Future JobsJian Qin
Data deluge has become a reality in today's scientific research. What does it mean to future science workforce? How can you prepare yourself to embrace the data challenges and opportunities? This presentation will provide you with an overview of data science and what it means to you as future researchers and career scientists.
The document discusses how large amounts of data generated from various sources globally can be processed and exploited using data science, artificial intelligence, machine learning and deep learning. These techniques help decision makers make more accurate and efficient decisions. Specifically, it discusses how structured, unstructured and semi-structured data from a variety of sources can be extracted, transformed and loaded into a data warehouse for analysis. It then provides overviews of artificial intelligence, machine learning, deep learning and data science and how they can be used together to solve real-world problems by learning from data.
Pdf wp-emc-mozyenterprise-hybrid-cloud-backuplverb
This document discusses hybrid backup architectures that use both on-premises and cloud-based technologies for data protection. A hybrid approach protects data in the data center locally but also uses the cloud to back up data from remote offices and mobile devices. This provides comprehensive data protection while reducing management burdens. The document recommends looking for a hybrid solution that ensures recoverability, is manageable by IT, supports remote workers, and increases productivity through secure access to files from any device.
This document summarizes a presentation on challenges and solutions for research operations at Oak Ridge National Laboratory. It discusses defining an operations philosophy focused on directly supporting research. It also addresses developing a team approach with expertise at all levels, from subject matter experts to local support staff. Finally, it outlines taking a plan-based approach to focus areas to continuously improve operations while keeping research progressing efficiently.
The Diabetes Discovery Project at Austin Health aimed to use their Cerner EMR system to routinely test HbA1c levels on inpatients over 54 to identify undiagnosed and poorly controlled diabetes. Testing of over 5,000 patients found 5% had undiagnosed diabetes and 29% had known diabetes. Higher HbA1c levels were associated with increased hospital admissions and longer lengths of stay for surgical patients. The project demonstrated using health IT to identify diabetes management opportunities. Ongoing work includes refining protocols and expanding to other patient populations.
This document summarizes a presentation on using data and informatics to improve allied health services. It discusses the history of allied health and challenges with data collection. Examples are provided of projects in New Zealand that used data to enhance patient and clinician experiences, reduce hospital-acquired infections, and inform staffing needs. The presentation emphasizes standardizing data to facilitate benchmarking and applying knowledge gained from data analysis to drive improvements in allied health.
This document presents a proof of concept for using Twitter data to conduct syndromic surveillance for public health monitoring. It analyzed tweets containing the keyword "measles" between 2014-2015 and found 1,408 relevant tweets. The number of tweets mentioning measles was compared to confirmed measles cases from a national surveillance system, showing potential for Twitter data as an early warning system. However, limitations include using a single keyword and the free Twitter API. Future work proposed improving data collection, applying machine learning techniques, and validating tweets with other health data sources.
The document discusses using surface modelling and mapping techniques to analyze healthcare data. It provides three scenarios as examples: 1) Mapping KPIs regionally to identify opportunities for improvement, 2) Mapping data around a specific pharmacy to examine market penetration, and 3) Comparing the market penetration of two smoking cessation medications. Surface mapping allows easy visualization and comparison of multiple data layers, helps protect patient privacy, and can provide insights into how to optimize outcomes.
The document summarizes how providing laptop computers to clinicians in a community allied health service has enhanced clinical care. Each of the 20 clinicians was provided a laptop with mobile data and remote desktop access to complete administrative and electronic tasks in the community rather than returning to the office. This has increased efficiency by allowing timely and collaborative work, which has decreased stress on clinicians and allowed for more timely information sharing with children and families. Some challenges remain around the weight of laptops and continuing reliance on paper records. Future plans include providing iPads and moving to more paperless systems.
This document describes the development of an electronic workflow system called scope to improve surgical practice at a District Health Board (DHB) hospital. The goals were to seamlessly map the patient journey, accurately collect coded data, and leverage trusted data to inform clinicians. The system streamlines waiting lists, captures accurate operating notes, and facilitates morbidity and mortality meetings. Implementation across surgical specialties has achieved good compliance and uptake. Preliminary results found increased quality of notes, discussion of complications, and potential to change practice through advanced data analysis. In conclusion, scope has replaced a disconnected paper system with a seamless electronic solution that fully captures standardized data to improve surgical outcomes.
1. The document discusses how healthcare has progressed beyond just electronic medical records (EMRs) and is now focused on areas like mobile computing, health collaboration, cloud-based back office systems, health intelligence, and clinical grade communications.
2. It provides examples of how technology is enabling cross-campus collaboration, telehealth, clinical collaboration using medical devices and teleradiology, and clinical communications.
3. The document advocates for sustainable eHealth innovation beyond just EMRs and discusses how areas like health analytics, mobility for care, patient-centered care, and emerging technologies can further improve healthcare.
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1. Chapter 11, Guyton and Hall Textbook of Medical Physiology, 14th edition
2. Chapter 9, Human Physiology - From Cells to Systems, Lauralee Sherwood, 9th edition
3. Chapter 29, Ganong’s Review of Medical Physiology, 26th edition
4. Electrocardiogram, StatPearls - https://www.ncbi.nlm.nih.gov/books/NBK549803/
5. ECG in Medical Practice by ABM Abdullah, 4th edition
6. Chapter 3, Cardiology Explained, https://www.ncbi.nlm.nih.gov/books/NBK2214/
7. ECG Basics, http://www.nataliescasebook.com/tag/e-c-g-basics
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Interpretation and Adoption of the Concept of Enterprise-wide and Best of Breed Health IT within the New Zealand eHealth Community
1. UU/IT
Interpretation and Adoption of the
Concept of Enterprise-wide and Best
of Breed Health IT within the New
Zealand eHealth Community
Rebecka Janols1, Karen Day2 and
Martin Orr2
1Uppsala University 2Universityof Auckland
Department of National Institute for Health
Information Technology Innovation
@ UU/IT 2012-11-15 | #‹#›
3. UU/IT
eHealth in New Zeeland
Implemented in most areas
Complex puzzle of IT systems and applications
Same IT systems differently configured
Changes are required:
Hard to maintain
Expensive
To enable future developments
@ UU/IT 2012-11-15 | #‹#›
4. UU/IT
The NZ Health IT plan (2010)
“set priorities for regional and national IT
investments over a five-year period”
Shared care record that focuses on the patient and
is shared between the patient and involved care
providers.
DHBs in the same region need to come together
and agree on a common platform (i.e. a standard
set of software that is used within the region).
@ UU/IT 2012-11-15 | #‹#›
5. UU/IT
“The aim of this paper is to unbundle what
Enterprise-wide and Best of Breed IT means in
the New Zealand health context.”
@ UU/IT 2012-11-15 | #‹#›
6. UU/IT
Methods
Review of key documents and relevant research
14 participants from different organisations with
different roles
Clinical Hospital manager/ Service
education IT manager Research Organisation Vendor
1 x x
2 x
3 x
4 (x) x
5 x
6 x x
7 (x) x
8 (x) x
9 (x) x
10 (x) x
11 x
12 x x
13 x x
14 x x
@ UU/IT 2012-11-15 | #‹#›
7. UU/IT
The participants‟ interpretation
“Enterprise sounds like you have one
significant and large all-encompassing
process, program, software. Best of Breed
you are going to have different parts of
different programs attached to maybe a
central source…”
@ UU/IT 2012-11-15 | #‹#›
8. UU/IT
Enterprise-wide is based on
“best practice”
“They have actually looked at: ‘what is
health care? What are we trying to do?
What are the basic sets? How does
medicine really work?’…”
@ UU/IT 2012-11-15 | #‹#›
9. UU/IT
Research definition: Enterprise systems
Health care Enterprise
system system
“Enterprise systems are
commercial software Reality
packages that enable the Enterprise
integration of transactions- system
oriented data and business
processes throughout an
organisation.”
Marcus and Tanis (2000)
@ UU/IT 2012-11-15 | #‹#›
10. UU/IT
Research definition: 'Best of Breed‟
Health care
system
“In the „best of breed‟
approach, the organization
picks and chooses ERP
modules which best support
its business processes from
various vendors.”
Sumner and Bradley (2007)
@ UU/IT 2012-11-15 | #‹#›
11. UU/IT
Best of Breed systems
Benefits Disadvantages
Customised to a particular Hard to integrate
purpose Hard to share data
Easier to implement change A complex network of
Flexibility system
A degree of individualisation Problems with upgrading to
newer versions
To many vendors
Cost – too expensive to
maintain.
Innovations stops
Security holes between the
system
@ UU/IT 2012-11-15 | #‹#›
12. UU/IT
Enterprise-wide systems
Benefits Disadvantages
Built on "best practice” „Best practice‟ is defined by
Easy to share and access the vendor not the users
detailed data Need to compromise – “one
One patient – one record size fits all”
Easier to manage Flexibility – hard to change
Standardisation of the data Users need to adapt to the
Centrally held data base system
Ability to interface Harder to innovate
The same “Look and feel” Monopoly – little power over
the supplier
Security is integrated- not
adhoc Expensive
Less duplication
@ UU/IT 2012-11-15 | #‹#›
13. UU/IT
Enterprise-wide vs. Best of Breed
The disadvantages with the BoB are often
mitigated by an Enterprise-wide system.
The disadvantages with the enterprise
systems are often mitigated by the BoB.
What is the future solution?
Is the answer one or the other?
@ UU/IT 2012-11-15 | #‹#›
14. UU/IT
CONCLUSION 1
‘Best practice’ can be differently interpreted.
@ UU/IT 2012-11-15 | #‹#›
15. UU/IT
Research definition: 'Best practice‟
‘‘The better or best ways of performing a
particular process’’
O‟Leary (2000)*
* O‟Leary DE. Enterprise resource planning systems: systems, life cycle, elecronic commerce
and risk. (Cambridge)
@ UU/IT 2012-11-15 | #‹#›
16. UU/IT
1. „Best practice‟ defined by the users
Health care
system
@ UU/IT 2012-11-15 | #‹#›
17. UU/IT
1. „Best practice‟ defined by the users
Health care “Vision”
system
“Reality”
@ UU/IT 2012-11-15 | #‹#›
18. UU/IT
2. „Best practice‟ for a process
Process X
(Org 1)
Process X IT-system
(Org 2)
process X
(Org 3)
‘‘One process – one system’’
@ UU/IT 2012-11-15 | #‹#›
19. UU/IT
3. Evaluated “best practice”
“.. it has gone through some form of
evaluations and inspections as being the
preferred option”
@ UU/IT 2012-11-15 | #‹#›
20. UU/IT
Does ‘best practice’ exist?
“The idea of best practice builds on the
assumption that there are certain solutions
that are superior compared to others when
solving problems in a certain context. “
Axelsson et al. (2012)*
* Axelsson K., Melin U. and Söderström F. (2012) Analyzing best practice and critical
success factors in a health information system case - are there any shortcuts to
successful IT implementation? In. 19th European Conference on Information
Systems.
@ UU/IT 2012-11-15 | #‹#›
21. UU/IT
Don‟t forget
“Since every organization is unique and has its
certain conditions there are obvious risks that
some of the built-in (best practice) actions and
processes in an IT system do not suit the
organization.“
Axelsson et al. (2012)*
* Axelsson K., Melin U. and Söderström F. (2012) Analyzing best practice and critical
success factors in a health information system case - are there any shortcuts to
successful IT implementation? In. 19th European Conference on Information
Systems.
@ UU/IT 2012-11-15 | #‹#›
22. UU/IT
CONCLUSION 2
All user groups have different
responsibilities, requirements and needs. A
enterprise-wide system is too generic to
adequately meet all users needs.
@ UU/IT 2012-11-15 | #‹#›
23. UU/IT
Findings: Enterprise-wide
systems
can be “too generic”
“The risk is that you develop something that is
so generic that it isn’t particularly useful to
the people who need to use it in a day-to-day
basis. That it collects data at a population
level, a district level…”
@ UU/IT 2012-11-15 | #‹#›
24. UU/IT
Who are the users?
“Everybody!”
@ UU/IT 2012-11-15 | #‹#›
25. UU/IT
Who are the users?
Administrative GPs
staff Physiotherapists
Managers PMOs
Government
DHBs Nurses
“Everybody!”
Physiologists
Hospital physicians
Assistant nurses
Researchers
Patients
@ UU/IT 2012-11-15 | #‹#›
26. UU/IT
What are data used for?
Administrative GPs
staff Physiotherapists
Research
Managers Clinical practice
PMOs
Government
DHBs Nurses
Measure quality “Everybody!”
Physiologists Inform founding
Statistics Hospital physicians
Planning Long term disease register
Assistant nurses
Measure outcome Researchers
Patients
Measure progress
@ UU/IT 2012-11-15 | #‹#›
27. UU/IT
Can all users‟ requirements be
supported by the same system?
Or does
responsibilities, roles, contextual
settings and traditions matter?
@ UU/IT 2012-11-15 | #‹#›
28. UU/IT
CONCLUSION 3
Enterprise-wide vs. BoB is a false dichotomy.
Need to identify what must be customised
and what can be centralised.
@ UU/IT 2012-11-15 | #‹#›
30. UU/IT
Future solution 1
“…maybe an enterprise-wide solution but it
allows local adaptation for those users in
different areas/…/I think that they both [ERP
and BoB] have risks and they both have
potentials in them. The devil is in the detail.”
@ UU/IT 2012-11-15 | #‹#›
31. UU/IT
Future solution 2
“…the core aspects of data and functionalities
are placed in an accessible location and they
then feed some of those systems. Then, if it
suits me to have an enterprise
system, absolutely fine, go for it/…/I think
that gives freedom to innovate around the
edge.”
@ UU/IT 2012-11-15 | #‹#›
32. UU/IT
3 conclusions
1. There is not a shared understanding of what
„Best practice‟ means.
2. A enterprise-wide system is too generic to
adequately meet all users needs.
3. Enterprise-wide vs. Best of Breed is a false
dichotomy. The challenge is to identify what
must be customised and what can be
centralised.
@ UU/IT 2012-11-15 | #‹#›
33. UU/IT
Thanks for your attention!
Questions?
Please contact me for future cooperation!
Rebecka.Janols@it.uu.se
@ UU/IT 2012-11-15 | #‹#›
Editor's Notes
Research interests: Human Computer Interaction, usability, user centeredness, change management and health informatics.Interviews, observations, evaluations and surveys at several Swedish county councils.Gain knowledge of user adoption when deploying and using enterprise-wide health IT systems.
Towards consistency, patient centeredness and a shared care record.
Questions:Their background and experiences related to this subjectInterpretation of the terms "enterprise-wide" and best of breed ITBenefits and risksReasons for choosing/not choosing the different solutionsIdentify user groups, their needs and requirements
Not all participantshadheard the two terms. Butwhen I askedthemtodefinethem, almost all gave the same definition.“Enterprise sounds like you have one significant and large all-encompassing process program, software. Best of Breed you are going to have different parts of different programs attached to maybe a central source. So you actually attach a skeleton, framework, as suppose to ‘one of everything’ is done by this particular program or software.”
Some said that it is based on a deeper thinking – not just modules interlinked by the vendor. You can almost say that the vendor have identified a best practice for delivering health care.“They have actually looked at: ‘what is health care? What are we trying to do? What are the basic sets? How does medicine really work?’That to me is an ‘enterprise-wide thing’. Not a whole lot of different modules were the vendor is just interlinking them, because we could have done that as well.”
*Marcus L. and Tanis C. (2000) The Enterprise System Experience - From Adoption to Success in Framing the Domains of IT Management: Projecting the Future Through the Past
Traditionally: BoB have been selected by the users – the clinicians
Research definition.In the research we found Findings: Three ways of defining ‘Best Practice’
“… each person responsible for that particular function chooses the computer software that best meets their needs to deliver to their function.”
“… each person responsible for that particular function chooses the computer software that best meets their needs to deliver to their function.”
All said that they had a BoB tradition – that the clinicians had been powerful in the decision. Discussion about Best practice, what is Best practice.“It was always ‘my opinion’- rules/…/ that is really silly, we don’t have the money to do that/…/ there must be some logic why that one is better than that one/…/ you need to agree what the best of breed is.”
*Marcus L. and Tanis C. (2000) The Enterprise System Experience - From Adoption to Success in Framing the Domains of IT Management: Projecting the Future Through the Past
When you are talking about best practice you talk about that there is one way that is better than another. The question is according to who? Who decides what is the best way??
“the pre-packaged solutions to reach success might turn out to be shortcuts that do not work in a situated practice.“ Axelsson (2012)
This quote is from a researcher - The answer lies in the middleClinicians have been to dominantThe clinicians needs have not been listen to.
Shared repository
I’m submitting my PhD early next year and are loocking for oppertunites to be a part of the future ehealth development in NZ.What should we do in NZ?I’m not saying that it is bad that you are cooperating between the DHBs. However it is important to realise that it can be a reason that they have selected different systems, not just because they want to be uniqe. And there is an advantage that they are used to the system. Changing system takes time, money and energy. be aware of the risks – not just buy the solutions on the benefits. I want in this presentation highlight that there is a debate, and that it is more complex than people think. And there is no consensus. false dichotomy.3Ccore (backbone) common (lab portal) customized (particular services have special needs).every strategy have pros and cons - you pick if for the pros - some other needs to take care of the cons. need to think about the cons. pros cons and compromises. space - I have not been involved in that. The procurement are important and I agree with what I know about active procurements. Important to have a broad picture – but it is also important that you are aware of that there is different users and they have different needs. And compromising their needs might be a short cuts that doesn’t work!I understand the question like that. Refraze the question. from what i have learned in this research. Is it good that the DHBs are working together? Or are they loosing their individuallity?