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Software Functionality Revealed in Detail
We’ve opened the hood on every major category of enterprise software. Learn about thousands of features and functions, and how enterprise software really works.
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Visit the TEC store to compare leading software solutions by funtionality, so that you can make accurate and informed software purchasing decisions.
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 level zero data flow diagram


Network Data Protection Playbook: Network Security Best Practice for Protecting Your Organization
Malicious hacking and illegal access are just a few of the reasons companies lose precious corporate data every year. As the number of network security breaches

level zero data flow diagram  provide information, tools and high-level reference architectures on how to protect data as well as to share CipherOptics' experience in providing data protection solutions around the world. The Nature and Source of Data Breaches We are in an era where IT departments are making headlines-unfortunately for all the wrong reasons. Data security breaches are growing, now affecting 90 percent of corporations and causing $17 billion in damage every year (Harvard Business Review). Vulnerabilities are

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Software Functionality Revealed in Detail

We’ve opened the hood on every major category of enterprise software. Learn about thousands of features and functions, and how enterprise software really works.

Get free sample report
Compare Software Solutions

Visit the TEC store to compare leading software by functionality, so that you can make accurate and informed software purchasing decisions.

Compare Now

HCIMS - Clinical Information System RFI/RFP Template

ADT (admission, discharge, and transfer), Global Requirements, Patient Information, Orders, Plan of Care, Work Plan, Kardex and Summary, Flow Sheets and Vitals, MAR and Medications, Critical Care, L&D Fetal Monitoring, Clinical Record, Reference and Reports, HIPAA (Health Insurance Portability and Accountability Act), Interfaces, Ease of Use, Technical and Support, and Product Technology  

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How to Achieve Lean Manufacturing


Lean manufacturing is a transformational exercise that requires an organization to cast aside long-held beliefs and business processes. The five main steps to achieving lean transition are defining value, mapping the value stream, making the activities flow, responding to customer demand, and continuous improvement.

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AuraPortal: A BPM Vendor Worth Checking Out


AuraPortal, a new business process management (BPM) vendor, offers a solution that creates business process execution models without the need for heavy IT programming. In this article, Principal Analyst P.J. Jakovljevic gives inside view of the vendor’s development strategies and the broad scope of BPM suite’s modules, and discusses how the system’s differentiating features addresses the diverse needs of its customers.

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4 Steps to a Best-run Business


To promote fast growth, small businesses often sacrifice process control for creativity. But sooner or later, unstructured creativity compounded by fast growth leads to the inability to make fact-based business decisions. Learn about four steps to developing a business strategy that can help you run your business more effectively by applying better control over your cost structure, minimizing risk, and anticipating change.

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Lean Manufacturing: Reaping the Rewards of Lean through Response Management


For years, manufacturers have been driven by sales forecasts and the need to maximize production efficiency at every level of operation. But in order to be successful, manufacturers must look toward adopting a lean mentality. While lean techniques are more easily applied to some manufacturing styles than others, new software tools are now able to deliver the benefits of lean to both high-mix and low-volume operations.

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Making Big Data Actionable: How Data Visualization and Other Tools Change the Game


To make big data actionable and profitable, firms must find ways to leverage their data. One option is to adopt powerful visualization tools. Through visualization, organizations can find and communicate new insights more easily. Learn how to make big data more actionable by using compelling data visualization tools and techniques.

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Distilling Data: The Importance of Data Quality in Business Intelligence


As an enterprise’s data grows in volume and complexity, a comprehensive data quality strategy is imperative to providing a reliable business intelligence environment. This article looks at issues in data quality and how they can be addressed.

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Enterprise Data Management: Migration without Migraines


Moving an organization’s critical data from a legacy system promises numerous benefits, but only if the migration is handled correctly. In practice, it takes an understanding of the entire ERP data lifecycle combined with industry-specific experience, knowledge, and skills to drive the process through the required steps accurately, efficiently, and in the right order. Read this white paper to learn more.

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10 Errors to Avoid When Building a Data Center


In the white paper ten errors to avoid when commissioning a data center, find out which mistakes to avoid when you're going through the data center...

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Addressing the Complexities of Remote Data Protection


As companies expand operations into new markets, the percentage of total corporate data in remote offices is increasing. Remote offices have unique backup and recovery requirements in order to support a wide range of applications, and to protect against a wide range of risk factors. Discover solutions that help organizations protect remote data and offer extensive data protection and recovery solutions for remote offices.

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Data Quality Strategy: A Step-by-Step Approach


To realize the benefits of their investments in enterprise computing systems, organizations must have a detailed understanding of the quality of their data—how to clean it and how to keep it clean. Those organizations that approach this issue strategically will be successful. But what goes into a data quality strategy? This paper from Business Objects, an SAP company, explores the strategy in the context of data quality.

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