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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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 level 0 data flow


Reinventing Data Masking: Secure Data Across Application Landscapes: On Premise, Offsite and in the Cloud
Be it personal customer details or confidential internal analytic information, ensuring the protection of your organization’s sensitive data inside and outside

level 0 data flow  Delphix Agile Masking, data masking, data security, security concerns, production environments, masking solution

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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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Thinking Radically about Data Warehousing and Big Data: Interview with Roger Gaskell, CTO of Kognitio


Managing data—particularly in large numbers—still is and probably will be the number one priority for many organizations in the upcoming years. Many of the traditional ways to store and analyze large amounts of data are being replaced with new technologies and methodologies to manage the new volume, complexity, and analysis requirements. These include new ways of developing data warehousing, the

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Data Management and Business Performance: Part 1-Data


Research for one of my projects led me to ask both software vendors and customers about the factors most important to software users in the selection of a business intelligence (BI) solution. Two topics resounded: the use of BI tools to improve data management and business performance management. Consumers are continuously looking for innovative ways to move, store, and improve the quality of

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Data Migration Management: A Methodology to Sustaining Data Integrity for Going Live and Beyond


For many new system deployments, data migration is one of the last priorities. Data migration is often viewed as simply transferring data between systems, yet the business impact can be significant and detrimental to business continuity when proper data management is not applied. By embracing the five phases of a data migration management methodology outlined in this paper, you can deliver a new system with quality data.

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Master Data Management and Accurate Data Matching


Have you ever received a call from your existing long-distance phone company asking you to switch to its service and wondered why they are calling? Chances are the integrity of its data is so poor that the company has no idea who many of its customers are. The fact is, many businesses suffer from this same problem. The solution: implement a master data management (MDM) system that uses an accurate data matching process.

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New Data Protection Strategies


One of the greatest challenges facing organizations is the protection of corporate data. The issues complicating data protection are compounded by increased demand for data capacity and higher service levels. Often these demands are coupled with regulatory requirements and a shifting business environment. Learn about data protection strategies that can help organizations meet these demands while maintaining flat budgets.

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A Road Map to Data Migration Success


Many significant business initiatives and large IT projects depend upon a successful data migration. But when migrated data is transformed for new uses, project teams encounter some very specific management and technical challenges. Minimizing the risk of these tricky migrations requires effective planning and scoping. Read up on the issues unique to data migration projects, and find out how to best approach them.

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Linked Enterprise Data: Data at the heart of the company


The data silos of today's business information systems (IS) applications, and the pressure from the current economic climate, globalization, and the Internet make it critical for companies to learn how to manage and extract value from their data. Linked enterprise data (LED) combines the benefits of business intelligence (BI), master data management (MDM), service-oriented architecture (SOA), and search engines to create links among existing data, break down data walls, provide an open, secure, and long-term technological environment, and reduce complexity—read this white paper to find out how.

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Achieving a Successful Data Migration


The data migration phase can consume up to 40 percent of the budget for an application implementation or upgrade. Without separate metrics for migration, data migration problems can lead an organization to judge the entire project a failure, with the conclusion that the new package or upgrade is faulty--when in fact, the problem lies in the data migration process.

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Understanding the PCI Data Security Standard


The payment card industry data security standard (PCI DSS) defines a comprehensive set of requirements to enhance and enforce payment account data security in a proactive rather than passive way. These include security management, policies, procedures, network architectures, software design, and other protective measures. Get a better understanding of the PCC DSS and learn the costs and benefits of compliance.

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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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