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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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 data flow diagram design exercise


How to Achieve Lean Manufacturing
Lean manufacturing is a transformational exercise that requires an organization to cast aside long-held beliefs and business processes. The five main steps to

data flow diagram design exercise  signals and the requisite data collection as the actual products flow through the supply chain. This would increase transparency and avoid stock bullwhip effects across the entire supply chain. A good example would be a repetitive scheduling technique like customer delivery schedule (CDS), which supports repetitive demands for one or several items to one or several locations in one transaction for discrete times or time buckets. Such schedule level management tools can enable users to receive demands

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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

Core PLM for Discrete Industries

The foundation of product lifecycle management (PLM) for the discrete manufacturing industries is product data management (PDM). It covers design and product-related aspects of PLM including management of material specifications, product structures, production processes, design tools, document management, and design collaboration. 

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Documents related to » data flow diagram design exercise

Demand Planning: Optimizing Operations across the Supply Chain


Demand planning applications can help manufacturers establish baseline sales forecasts and perform analysis to improve resource usage. They can also help manufacturers optimize pricing capabilities and better understand their markets. Yet to get the most out of these tools, manufacturers must be willing to reorganize their planning processes—and to share the resulting insights with supply chain partners and customers.

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Data Management and Analysis


From a business perspective, the role of data management and analysis is crucial. It is not only a resource for gathering new stores of static information; it is also a resource for acquiring knowledge and supporting the decisions companies need to make in all aspects of economic ventures, including mergers and acquisitions (M&As).

For organizational growth, all requirements and opportunities must be accurately communicated throughout the value chain. All users—from end users to data professionals—must have the most accurate data tools and systems in place to efficiently carry out their daily tasks. Data generation development, data quality, document and content management, and data security management are all examples of data-related functions that provide information in a logical and precise manner.

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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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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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Addressing the Complexities of Remote Data Protection


As companies expand operations into new markets, the percentage of total corporate data in remote offices is increasing. Remote offices have unique backup and recovery requirements in order to support a wide range of applications, and to protect against a wide range of risk factors. Discover solutions that help organizations protect remote data and offer extensive data protection and recovery solutions for remote offices.

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Data Storage in the Cloud--Can You Afford Not To?


In Data Storage in the Cloud Can You Afford Not To?

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Massive Data Requires Massive Measures


One thing we learned in the data warehouse and data management world is that when it comes to the analysis of big data, there is also a lot of big money involved in order to gain position. But is the analysis of extensive amounts of data really a key component for the corporate business world?

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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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Data Governance: Controlling Your Organization’s Mission-critical Information


Controlling your company’s key information through data governance is more than just good practice—it can make the difference between success and failure at meeting compliance requirements and at arming your organization with a competitive edge.

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Oracle Database 11g for Data Warehousing and Business Intelligence


Oracle Database 11g is a database platform for data warehousing and business intelligence (BI) that includes integrated analytics, and embedded integration and data-quality. Get an overview of Oracle Database 11g’s capabilities for data warehousing, and learn how Oracle-based BI and data warehouse systems can integrate information, perform fast queries, scale to very large data volumes, and analyze any data.

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