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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 warehouse wiki


Role of In-memory Analytics in Big Data Analysis
Organizations today need to handle and manage increasingly large volumes of data in various formats and coming from disparate sources. Though the benefits to be

data warehouse wiki  In-memory Analytics in Big Data Analysis In a previous article , I discussed big data and the need for a big data solution to handle, manage, and derive valuable insight from large volumes of data in various formats and coming from disparate sources. Here I discuss the role that in-memory technologies plays in big data analysis and the potential of this technology to change the business intelligence (BI) landscape and the industry technology space. But first we need to understand the basics.   A Basic

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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

Warehouse Management Systems (WMS)

A warehouse management system (WMS) should provide database and user-level tools in order for a company to optimize its storage facilities while at the same time providing user level task direction and activity support. The WMS should enable warehouse operators to optimize pick, put-away, and replenishment functions by employing powerful system logic to select the best locations and sequences. 

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Documents related to » data warehouse wiki

BI State of the Market Report


IT departments rarely know as much about a business as the business people themselves. But business users still depend on IT to deliver answers related to the information that they receive. Learn how business intelligence (BI) 2.0—also known as collaborative BI—is helping business users create and modify their own reports, share and enrich information, and provide feedback to each other and to information producers.

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A How-to Guide for a Radio Frequency Identification Site Survey


As organizations prepare for a radio frequency identification (RFID) implementation, they often don't understand the preliminary work necessary to begin the project. The importance of a site survey can influence the success or failure of an RFID project.

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Business Intelligence: A Guide for Midsize Companies


Business intelligence (BI) is not a new concept. What’s new is that BI tools are now accessible for midsize companies. Managers can use BI to analyze complex information to support their decision-making processes, combining data from a variety of sources to get an integrated, 360-degree view of the company. Find out how to select the right BI software, the right vendor, and the right approach to implementing BI.

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Reconnecting with a Tried-and-True Manufacturing ERP Vendor


What has QAD, a leading provider of enterprise applications for global manufacturing companies, been up to lately? TEC principal analyst P.J. Jakovljevic reconnects with QAD and looks at how the company has leveraged strategic channels, highly scalable solutions, and technology partnerships to address the unique requirements global manufacturers and maintain a competitive position in the global manufacturing ERP market.

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Types of Prefabricated Modular Data Centers


Data center systems or subsystems that are pre-assembled in a factory are often described with terms like prefabricated, containerized, modular, skid-based, pod-based, mobile, portable, self-contained, all-in-one, and more. There are, however, important distinctions between the various types of factory-built building blocks on the market. This paper proposes standard terminology for categorizing the types of prefabricated modular data centers, defines and compares their key attributes, and provides a framework for choosing the best approach(es) based on business requirements.

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Warehouse Management Systems: Pie in the Sky or Floating Bakery?Part Two: The Pareto Principle, Processes, and People: Assessing Your Warehouse Management System Needs


To ensure your warehouse management system is implemented as painlessly as possible, you must assess your warehouse situation before you decide on a warehouse solution. Using the Pareto Principle, where a minority of inputs yields the majority results; examining your processes; evaluating your personnel; monitoring the progress of implementation; and testing are the best ways to ensure both a successful launch and long term return on investment.

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Data Center Projects: Project Management


In data center design projects, flawed management frequently leads to delays, expense, and frustration. Effective project management requires well-defined responsibilities for every manager, tight coordination among suppliers, well-defined procedures for managing change, and consistent terminology. Learn how enforcing these requirements can help your company achieve an efficient process with a predictable outcome.

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Data Security Is Less Expensive than Your Next Liability Lawsuit: Best Practices in Application Data Security


Insecure data. Heavy fines due to non-compliance. Loss of customers and reputation. It adds up to a nightmare scenario that businesses want to avoid at all costs. However, this nightmare is preventable: knowledge base-driven data security solutions can be critical tools for enterprises wanting to secure not only their data—but also their status in the marketplace.

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Protecting Critical Data


The first step in developing a tiered data storage strategy is to examine the types of information you store and the time required to restore the different data classes to full operation in the event of a disaster. Learn how in this white paper from Stonefly.

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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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