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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 definition necessity


Access to Critical Business Intelligence: Challenging Data Warehouses?
There is a perception that if business users are given access to enterprise databases and raw query tools, they will create havoc in the system, which is a

data warehouse definition necessity  be conducted without a data warehouse (DW). Indeed, when companies are dealing with a deluge of data, it helps to have a DW, since it offers large corporations the ability to leverage information assets to support enterprise reporting and analysis. DWs also provide a technical solution to the problem of multiple systems, separate data stores, and rapidly expanding historical data, since information is extracted from various transaction-based systems, such as spreadsheet, enterprise resource planning (

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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

Discrete Manufacturing (ERP)

The simplified definition of enterprise resource planning (ERP) software is a set of applications that automate finance and human resources departments and help manufacturers handle jobs such as order processing and production scheduling. ERP began as a term used to describe a sophisticated and integrated software system used for manufacturing. In its simplest sense, ERP systems create interactive environments designed to help companies manage and analyze the business processes associated with manufacturing goods, such as inventory control, order taking, accounting, and much more. Although this basic definition still holds true for ERP systems, today its definition is expanding. Today’s leading ERP systems group all traditional company management functions (finance, sales, manufacturing, and human resources). Many systems include, with varying degrees of acceptance and skill, solutions that were formerly considered peripheral such as product data management (PDM), warehouse management, manufacturing execution system (MES), and reporting. During the last few years the functional perimeter of ERP systems began an expansion into its adjacent markets, such as supply chain management (SCM), customer relationship management (CRM), business intelligence/data warehousing, and e-business, the focus of this knowledge base is mainly on the traditional ERP realms of finance, materials planning, and human resources. The foundation of any ERP implementation must be a proper exercise of aligning customers'' IT technology with their business strategies, and subsequent software selection. 

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Documents related to » data warehouse definition necessity

Collaborative Logistics Technology: Filling the Competency Gap


It’s not just operating talent and facilities that win business for logistics service providers. Every community of clients, customers, suppliers, and carriers must work together to fulfill perfect orders. However, few supply chain communities consist entirely of companies with top-notch supply chain applications. Learn how a software-as-a-service (SaaS) solution can help fill the gaps—and increase value to your clients.

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Dealing with Chaos: 4 Steps to Manufacturing Success


Manufacturing today is fraught with uncertainties in the supply chain due to a variety of global issues, including weather and exchange rates. You can counter supply problems with “safety stock.” But this extra inventory goes against the rules of an efficient lean environment. How can you stay demand driven, without a supply snafu? Find out how an information management system can help forecast your supply chain needs.

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Nine Telltale Signs You Should Replace Your Current WMS


You rely on a warehouse management system (WMS) to maintain ongoing operations, support changing customer requirements, keep up with industry regulations, and simply get product out the door on a daily basis. But a faltering system may also be constraining your global potential. Find out how to determine if your current WMS system is hindering your ability to execute business strategies that help you grow your business.

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Discussing the S&OP State of Affairs with Logility’s Karin Bursa


My recent exhaustive series of articles on sales @ operations planning (S@OP) entitled “APICS 2009 From the Expo Floor: Is S@OP Coming of Age?” and the related blog post entitled “Linking S@OP and CPFR (For Retailers and Manufacturers Sake): An Executive Panel Discussion” have drawn solid interest and valuable feedback. But even more, this prolonged exposure on the S@OP

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The Teradata Database and the Intelligent Expansion of the Data Warehouse


In 2002 Teradata launched the Teradata Active Enterprise Data Warehouse, becoming a key player in the data warehouse and business intelligence scene, a role that Teradata has maintained until now. Teradata mixes rigorous business and technical discipline with well-thought-out innovation in order to enable organizations to expand their analytical platforms and evolve their data initiatives. In this report TEC Senior BI analyst Jorge Garcia looks at the Teradata Data Warehouse in detail, including functionality, distinguishing characteristics, and Teradata's role in the competitive data warehouse space.

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Considerations for Owning versus Outsourcing Data Center Physical Infrastructure


When faced with the decision of upgrading an existing data center, building new, or leasing space in a retail colocation data center, there are both quantitative and qualitative differences to consider. The 10-year TCO may favor upgrading or building over outsourcing; however, this paper demonstrates that the economics may be overwhelmed by a business’ sensitivity to cash flow, cash crossover point, deployment timeframe, data center life expectancy, regulatory requirements, and other strategic factors. This paper discusses how to assess these key factors to help make a sound decision.

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Re-think Data Integration: Delivering Agile BI Systems with Data Virtualization


Today’s business intelligence (BI) systems have to change, because they’re confronted with new technological developments and new business requirements, such as productivity improvement and systems as well as data in the cloud. This white paper describes a lean form of on-demand data integration technology called data virtualization, and shows you how deploying data virtualization results in BI systems with simpler and more agile architectures that can confront the new challenges much easier.

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How to Comply with Data Security Regulations


A remote data backup solution can be compliant with almost any international, federal, or state data protection regulation—and can be compliant with the common caveats of most data security laws by providing functionality like data encryption and secure media control. And, as some regulations require files to be archived for several years, you can create a routine that archives files you select for backup and storage.

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Top 10 Evaluation Criteria for Copy Data Management & Data Virtualization


Data virtualization is becoming more important, as industry-leading companies learn that it delivers accelerated IT projects at a reduced cost. With such a dynamic space, one must make sure that vendors will deliver on their promises. This white paper outlines 5 qualification questions to ask before and during the proof of concept (POC), and 5 things to test during the POC.

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2013 Big Data Opportunities Survey


While big companies such as Google, Facebook, eBay, and Yahoo! were the first to harness the analytic power of big data, organizations of all sizes and industry groups are now leveraging big data. A survey of 304 data managers and professionals was conducted by Unisphere Research in April 2013 to assess the enterprise big data landscape, the types of big data initiatives being invested in by companies today, and big data challenges. Read this report for survey responses and a discussion of the results.

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