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Developing a Universal Approach to Cleansing Customer and Product Data
Data quality has always been an important issue for companies, and today it’s even more so. But are you up-to-date on current industry problems concerning data

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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 or...
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Documents related to » food beverage production data flow diagram


Overall Approach to Data Quality ROI
Data quality is an elusive subject that can defy measurement and yet be critical enough to derail any single IT project, strategic initiative, or even a company

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Transactional Data: Driving Real-Time Business
A global survey of IT leaders shows that most organizations find it challenging to convert high volumes of fresh transactional data into knowledge that business

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Ensuring Food Safety and Brand Protection through Supply Chain Traceability
To ensure the safety of the domestic and global food supply, demands for brand protection assurance are on the rise, as are national and global food safety

food beverage production data flow diagram  Food Safety and Brand Protection through Supply Chain Traceability To ensure the safety of the domestic and global food supply, demands for brand protection assurance are on the rise, as are national and global food safety initiatives. Food processors and distribution warehouses up and down the supply chain now find automated traceability systems are a necessity. Learn about an automated approach to traceability that is both cost-effective and a good fit for existing business operations. Read More...
Data Management and Business Performance: Part 1-Data
Research for one of my projects led me to ask both software vendors and customers about the factors most important to software users in the selection of a

food beverage production data flow diagram   Read More...
Implementing Energy-Efficient Data Centers
But in the white paper implementing energy-efficient data centers, you'll learn how to save money by using less electricitywhether your data cente...

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Data Integration: Creating a Trustworthy Data Foundation for Business Intelligence
Organizations combine their historical data with current data from operational systems to satisfy business intelligence analysis and government reporting

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Enterprise Data Management: Migration without Migraines
Moving an organization’s critical data from a legacy system promises numerous benefits, but only if the migration is handled correctly. In practice, it takes an

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Data Masking: Strengthening Data Privacy and Security
Many business activities require access to real production data, but there are just as many that don’t. Data masking secures enterprise data by eliminating

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A Definition of Data Warehousing
There is a great deal of confusion over the meaning of data warehousing. Simply defined, a data warehouse is a place for data, whereas data warehousing

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Business Basics: Unscrubbed Data Is Poisonous Data
Most business software system changes falter--if not fail--because of only a few root causes. Data quality is one of these root causes. The cost of high data

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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

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Guidelines for Specification of Data Center Power Density
Conventional methods for specifying data center density don’t provide the guidance to assure predictable power and cooling performance for the latest IT

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Backing up Data in the Private Cloud: Meeting the Challenges of Remote Data Protection - Requirements and Best Practices
This white paper describes some of the common challenges associated with protecting data on laptops and at home and remote offices and portrays proven solutions

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Distilling Data: The Importance of Data Quality in Business Intelligence
As an enterprise’s data grows in volume and complexity, a comprehensive data quality strategy is imperative to providing a reliable business intelligence

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