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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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 water quality rfp


Getting It Right: ERP Solutions for Mixed-mode Manufacturers
Falling somewhere between discrete and process manufacturing, mixed-mode manufacturers haven’t always been well served by traditional discrete or process

water quality rfp  lubricant manufacturing automotive manufacturing water treatment manufacturing furniture manufacturing mining companies machines precision parts organic and inorganic chemicals electronics pigments   coatings and paints   inks and dyes   adhesive manufacturers   oil and gas fields   pool chemicals   cleaning products and solvents   pharmaceutical   food and beverage   biotechnology Table 1. Discrete and process manufacturing sectors. The Trouble with Traditional Discrete and Process ERP Systems

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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

ERP for Municipalities

In this model, we assume the municipality controls water, sewers and roads. We assume also that it collects municipal or county taxes and manages many of its own assets such as vehicles and water treatment plant. ERP software for Municipalities nearly always includes Finance, Customer Care and Billing For a complete municipal ERP suite, the following modules are usually included: - Human Resources - Maintenance Management - Asset Management - Project Management ( including Grant Management) - Quality Management - Analytics - Product Technology Of the above, Project and Quality Management modules may not be required for smaller Municipalities.    

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Scalable Data Quality: A Seven-step Plan for Any Size Organization


Every record that fails to meet standards of quality can lead to lost revenue or unnecessary costs. A well-executed data quality initiative isn’t difficult, but it is crucial to getting maximum value out of your data. In small companies, for which every sales lead, order, or potential customer is valuable, poor data quality isn’t an option—implementing a thorough data quality solution is key to your success. Find out how.

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Data Quality Trends and Adoption


While much of the interest in data quality (DQ) solutions had focused on avoiding failure of data management-related initiatives, organizations now look to DQ efforts to improve operational efficiencies, reduce wasted costs, optimize critical business processes, provide data transparency, and improve customer experiences. Read what DQ purchase and usage trends across UK and US companies reveal about DQ goals and drivers.

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Data Quality Basics


Bad data threatens the usefulness of the information you have about your customers. Poor data quality undermines customer communication and whittles away at profit margins. It can also create useless information in the form of inaccurate reports and market analyses. As companies come to rely more and more on their automated systems, data quality becomes an increasingly serious business issue.

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Poor Data Quality Means A Waste of Money


Data quality sounds like a motherhood and apple pie issue, of course we want our data to be right. However, very few enterprises get serious about it. Maybe that's because the cost of data quality is hidden. That cost can be huge.

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Quality of Service for Next-generation Voice Over IP Networks


In order to support the requirements of voice deployments, next-generation networks must be capable of supporting a service equivalent to the existing public switched telephone network (PSTN), in terms of reliability. Furthermore, these networks must be capable of carrying voice services even under heavy load, while maintaining the integrity of the voice calls, under even the most extreme circumstances.

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Increasing Sales and Reducing Costs across the Supply Chain-Focusing on Data Quality and Master Data Management


Nearly half of all US companies have serious data quality issues. The problem is that most are not thinking about their business data as being valuable. But in reality data has become—in some cases—just as valuable as inventory. The solution to most organizational data challenges today is to combine a strong data quality program with a master data management (MDM) program, helping businesses leverage data as an asset.

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Guide to Quality Assurance


In today’s world, current and future customers are interested to know whether or not you have implemented a quality control system. Some customers will demand International Organization for Standards (ISO) certification, and others may just ask about it. Whatever their requirements, having a quality control system assures your customers that the products and services you offer are of high quality.

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A Mobile Software Quality Framework: How Quality Can Accelerate “Speed-to-market”


Today’s mobile software companies face a daunting challenge: How can they achieve quality while getting to market swiftly? After all, speed is king in the mobile market. The trade-off between speed and quality in mobile software development is an illusion—or should be. Get a closer look at the situation with a framework that presents a way to use quality assurance (QA) processes to accelerate development.

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Turning Information and Data Quality Into Sustainable Business Value


Driven by a number of developments in society, the economy, and technology, corporate data management is increasingly gaining importance, and emerging technologies such as in-memory computing allow companies to make the best use of their data. This white paper gives guidance to companies undertaking this endeavor and provides a sound overview of corporate data quality management capabilities and practices.

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