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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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 data entry proposal


Ask the Experts: Data Purging and System Migration
One reader recently wrote in with this question:

data entry proposal  business intelligence studies. Summary data allows a look at a product’s sales figures for a given time period, by examining a single entry in a table rather then summing up individual sales order lines. System Migration Defining Your Needs A migration project often starts with a feasibility study, which takes place before an implementation project gets off the ground. The approval process can include the board of directors or a high-ranking officer who sponsored the feasibility study for the project.

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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

Outsourcing, IT Infrastructure

The IT Infrastructure Outsourcing knowledge base focuses on the selection of companies who provide outsource services in the areas of information technology (IT) infrastructure. The typical types of activities that these providers perform include data center operations; network operations; backup/recovery services, data storage management services; system administration services; end user support of desktop PCs, laptops, and handheld devices; web site, or application hosting, etc.  

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PDM vs. PLM: A Matrix View


Two recent blog posts by Oleg Shilovitsky (PDM vs. PLM: A Data Perspective and PDM vs. PLM: A Process Perspective) got me wondering about what a true product lifecycle management (PLM) system actually is. In his posts, Shilovitsky discussed the differences between product data management (PDM) and PLM from the perspective of data (scope and control of the data) and process (coverage of

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The Basics of Quote-to-order Systems


Global competition means more choice for consumers and increasing customer demands. Manufacturers and distributors must develop a better understanding of what customers want so that they can configure, produce, and deliver products and services faster and more cost-effectively.

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Quote-to-order: A Newcomer Causes a Stir in the Market


A crop of next-generation, Web-based, on-demand, startup quote-to-order systems providers has lately flourished, spearheaded by BigMachines, whereas some traditional vendors that once defined the product configuration space in the 1990s have since left the market.

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DoubleClick Takes Bath, Throws in Towel


After weeks of being deluged by lawsuits, bad press, federal regulatory investigations and nasty name-calling, DoubleClick backs off on its plans to tie surfing behavior to personally identifiable information.

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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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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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Next-generation Data Auditing for Data Breach Protection and Risk Mitigation


Data breaches and leaks are on the rise—and the consequences, from theft of identity or intellectual property, can seriously compromise a company’s reputation. Stolen laptops, hacking, exposed e-mail, insider theft, and other causes of data loss can plague your company. How can you detect (and respond!) to breaches and protect your data center? Learn about the functions and benefits of an automated data auditing system.

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Don't Be Overwhelmed by Big Data


Big Data. The consumer packaged goods (CPG) industry is abuzz with those two words. And while it’s understandable that the CPG world is excited by the prospect of more data that can be used to better understand the who, what, why, and when of consumer purchasing behavior, it’s critical CPG organizations pause and ask themselves, “Are we providing retail and executive team members with “quality” data, and is the data getting to the right people at the right time? Big Data can be a Big Deal - read this white paper for some useful tips on ensuring secure, quality data acquisition and management.

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The Operational Data Lake: Your On Ramp to Big Data


Companies recognize the need to integrate big data into their real-time analytics and operations, but this poses a lot of technical and resource challenges. Meanwhile, those organizations that have operational data stores (ODSs) in place find that, while useful, they are expensive to scale. The ODS gives real-time visibility into operational data. While more cost-effective than a data warehouse, it uses outdated scaling technology, and performance upgrades require very specialized hardware. Plus, ODSs just can't handle the volume of data that has become a matter of fact for businesses today.

This white paper discusses the concept of the operational data lake, and its potential as an on-ramp to big data by upgrading outdated ODSs. Companies that are building a use case for big data, or those considering an upgrade to their ODS, may benefit from this stepping stone. With a Hadoop relational database management system (RDBMS), companies can expand their big data practices at their own pace.

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Data Evolution: Why a Comprehensive Data Management Platform Supersedes the Data Integration Toolbox


Today’s organizations have incredible amounts of information to be managed, and in many cases it is quickly spiraling out of control. To address the emerging issues around managing, governing, and using data, organizations have been acquiring quite a toolbox of data integration tools and technologies. One of the core drivers for these tools and technologies has been the ever-evolving world of the data warehouse.

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