From Ebola preparedness to leading large-scale changes, today’s master’s degree programs are producing leaders eager to tackle this generation’s most pressing challenges.
Rahul Anand, MD, is chief epidemiologist at Middlesex Hospital in Middletown, Connecticut, where he heads up all infectious disease prevention activities for the nonprofit integrated delivery network, from Ebola preparedness to hand washing. He’s also adjunct assistant professor in the department of medicine at the University of Utah, where he worked full time prior to moving to the East Coast. On top of that, he is one-third of the way through an MBA program at the University of Massachusetts Isenberg School of Management. It will take him another two years to finish the online program.
Healthcare organizations are allocating significant dollars, time and resources to the implementation of electronic health records (EHRs). While several studies have estimated the cost to purchase and install an EHR to be anywhere between $15,000 to $70,000 per provider1, real-world implementations have soared into the billions.
Electronic health record (EHR) system implementation is one of the largest IT investments most healthcare systems have ever made but it’s success is largely dependent upon the data which feeds it. One the main data sources for the EHR is the item master, which drives not only supply chain processes but also a broad range of clinical and financial functions. Only with a clean, accurate and complete item master can a healthcare organization trust the outputs generated from its EHRs – from evaluating the clinical effectiveness of products to securing reimbursements. Learn how to execute a master data management strategy to derive the greatest value from your EHR investment.
A decade ago, hospital leaders viewed cost containment as a distant option to that of building topline revenue through increased volumes and rates. But with the road to profitability choked off by a recession, the ACA, and double-digit increases in healthcare inflation, most have been left pursuing a flurry of initiatives to cut operational costs and maintain positive margins.
TIBCO Data Virtualization é uma solução comprovada que é usada por quatro das cinco principais companhias de energia integradas para fornecer mais rapidamente um maior volume de dados analíticos nas operações de exploração e produção. Os casos de uso específicos descritos incluem:
• Análise de dados em plataformas offshore
• Manutenção e reparação de poços
• Serviços de dados web em refinarias
• SAP Master Data Quality
Se uma empresa de energia está enfrentando desafios relacionados com dados e suas análises, deve considerar o TIBCO Data Virtualization.
TIBCO Data Virtualization es una solución probada que es utilizada por cuatro de las cinco principales compañías de energía integradas para obtener más rápidamente una mayor cantidad de datos analíticos las operaciones de exploración y producción. Los casos de uso específicos que se describen incluyen:
• Analítica de Datos de Plataformas Marítimas
• Mantenimiento y Reparación de Pozos
• Servicios de Datos Web en Refinerías
• SAP Master Data Quality
Si una compañía de energía está enfrentando desafíos relacionados con los datos y la analítica similares, debe considerar TIBCO Data Virtualization.
Today, deep learning is at the forefront of most machine learning implementations across a broad set of business verticals. Driven by the highly flexible nature of neural networks, the boundary of what is possible has been pushed to a point where neural networks outperform humans in a variety of tasks, such as classifying objects in images or mastering video games in a matter of hours. This guide outlines the end-to-end deep learning process implemented on Amazon Web Services (AWS). We discuss challenges in executing deep learning projects, highlight the latest and greatest technology and infrastructure offered by AWS, and provide architectural guidance and best practices along the way.
This paper is intended for deep learning research scientists, deep learning engineers, data scientists, data engineers, technical product managers, and engineering leaders.
Published By: Zynapse
Published Date: Jun 16, 2010
Data Governance has emerged as the point of convergence for people, technology and process in order to manage the crucial data (information) of an enterprise. This is a vital link in the overall ongoing data management process for it maintains the quality of data and makes it available to a wide range of decision making hierarchy across an organization
Published By: Zynapse
Published Date: Sep 10, 2010
UNSPSC enables preference item management, better spend analysis, supply standardization and information control.
Whether you are deliberating on the need for a common product and classification standard for your company, or are an advanced UNSPSC adopter, we hope that "Adopting UNSPSC" will answer some of your questions and perhaps help you in some way to improve your purchasing and supply management processes.
Published By: Zynapse
Published Date: Aug 17, 2010
An exclusive success story of a Fortune 200 enterprise.
Learn how the master data management initiative delivered:
. A unified view of the master data across the enterprise
. Accelerated ROI realization from massive ERP investments
. Inventory optimization by duplicate identification
. Improved operational and process efficiencies
Published By: BambooHR
Published Date: Apr 11, 2016
HR processes affect how hard employees work, how well they perform, how happy they are in their work, and how loyal they are to their employers. And yet many small business leaders handle HR duties on their own. For those DIY business leaders we’ve created a DIY guide to master HR best practices.
Download this free ebook to learn how to not only DIY, but more importantly, how to DIW. That is to say: Do it well.
Although data and analytics are highlighted throughout the popular press as well as in trade publications, too many managers think the value of this data processing is limited to a few numerically intensive fields such as science and finance. In fact, big data and the insights that emerge from analyzing it will transform every industry, from “precision farming” to manufacturing and construction. Governments must also be alert to the value of data and analytics as the enabler for smart cities. Institutions that master available data will leap ahead of their less statistically adept competitors through many advantages: finding hidden opportunities for efficiency, using data to become more responsive to clients, and developing entirely new and unanticipated product lines. The average time spent by most companies on the S&P 500 Index has decreased from an average of 60 to 70 years to only 22 years. There are winners and losers in the changes that come with the evolution of both technology
Published By: Cisco EMEA
Published Date: Jun 01, 2018
Digital transformation has arrived, and it’s creating unprecedented opportunities for companies of all sizes to become market leaders through the evolution of business processes and the creation of new products and services. Organizations that master digital transformation will see a dramatic increase in revenues and profitability by converging people, processes and technologies; those that do not will struggle to survive. Evidence of this is clear to see by looking at the churn in the biggest
companies in the world. For example, a Capgemini study found that since 2000, 52% of the Fortune 500 has disappeared through acquisitions or bankruptcies. The study also found that digital organizations control 70% of market share in all industries today. Therefore, making the shift to a digital business must be a top initiative for IT and business leaders.
Download this whitepaper to see how Cisco has become the Market Share Leader in Online Meetings.
To better understand how companies are finding the unique, hybrid cloud architectures that best meet their needs, we interviewed executives at companies that had reduced or changed their use of managed or cloud IaaS or that chose to avoid the public cloud in the first place.
These companies include retail, social media, healthcare, financial services, and public sector companies. Some of these companies were born in the cloud while others transitioned from traditional IT infrastructures. Company sizes ranged from 300 employees to more than 300,000.