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Software Functionality Revealed in Detail
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 data flow design


Data, Data Everywhere: A Special Report on Managing Information
The quantity of information in the world is soaring. Merely keeping up with, and storing new information is difficult enough. Analyzing it, to spot patterns and

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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 design

Data Center Projects: System Planning


System planning is the Achilles’ heel of a data center physical infrastructure project. Planning mistakes can propagate through later deployment phases, resulting in delays, cost overruns, wasted time, and a compromised system. These troubles can be eliminated by viewing system planning as a data flow model, with sequenced tasks that progressively transform and refine data from initial concept to final design. Learn more.

data flow design  system planning as a data flow model, with sequenced tasks that progressively transform and refine data from initial concept to final design. Learn more. Read More

The Evolution of a Real-time Data Warehouse


Real-time data warehouses are common in some organizations. This article reviews the basic concepts of a real-time data warehouse and it will help you determine if your organization needs this type of IT solution.

data flow design  Right Time . The data must flow to the real-time data warehouse at the necessary speed in order to be considered valuable data. In a real-time data warehouse, the ETL batch mechanism based on a table or file transfer is replaced with a design in which data flows from very different yet synchronized data sources into the data warehouse. Data will be considered valuable if it flows at the right speed and not necessarily at real-time speed. This data cycle will depend on the analytical purpose the data is Read More

An Improved Architecture for High-efficiency, High-density Data Centers


Globally, data center power and cooling infrastructure wastes more than 60 million megawatt-hours per year that do not contribute usefully to powering IT equipment. This is an enormous financial burden on industry, and is a significant public policy environmental issue. Find out about the principles of a new data center architecture that can be implemented today to dramatically improve the electrical efficiency of your data center.

data flow design  future zone in a data center can be deferred until future IT deployment. Row-based cooling Improves cooling efficiency Row-based cooling places air conditioning within the rows of IT equipment, rather than at the perimeter of the room. Shortening the air flow path reduces mixing of hot and cold air streams which improves the predictability of air distribution. Predictable air distribution to IT equipment allows for more precise control of variable airflow rates that automatically adjust to the needs of Read More

New Data Triggers for International Supply Chain Finance


Corporations have drastically changed their global supply chain models over a short period. The market is also in the early stages of migrating to data triggered finance, creating opportunities for banks and logistic companies to develop international supply chain finance solutions.

data flow design  We believe Banks need data triggers to be smarter about payment and finance, and that means figuring out how to work with global transportation and logistics players. Banks will need to get smart about industry sectors and the global flow of suppliers, the tiered nature of specific supply chains, etc. The old formula of wallet , where banks measure market share by calculating a percentage of their corporate client's account, does not make as much sense in this global supply chain world. New credit and Read More

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 understanding of the entire ERP data lifecycle combined with industry-specific experience, knowledge, and skills to drive the process through the required steps accurately, efficiently, and in the right order. Read this white paper to learn more.

data flow design  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 understanding of the entire ERP data lifecycle combined with industry-specific experience, knowledge, and skills to drive the process through the required steps accurately, efficiently, and in the right order. Read this white paper to learn more. Read More

Thinking Radically about Data Warehousing and Big Data: Interview with Roger Gaskell, CTO of Kognitio


Managing data—particularly in large numbers—still is and probably will be the number one priority for many organizations in the upcoming years. Many of the traditional ways to store and analyze large amounts of data are being replaced with new technologies and methodologies to manage the new volume, complexity, and analysis requirements. These include new ways of developing data warehousing, the

data flow design  Radically about Data Warehousing and Big Data: Interview with Roger Gaskell, CTO of Kognitio Managing data—particularly in large numbers—still is and probably will be the number one priority for many organizations in the upcoming years. Many of the traditional ways to store and analyze large amounts of data are being replaced with new technologies and methodologies to manage the new volume, complexity, and analysis requirements. These include new ways of developing data warehousing, the Read More

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 users can efficiently access, understand, and act on. SAP and HP are tackling this challenge head-on. Download this article to learn more.

data flow design  volumes of fresh transactional data into knowledge that business users can efficiently access, understand, and act on. SAP and HP are tackling this challenge head-on. Download this article to learn more. Read More

Metagenix Reverse Engineers Data Into Information


Metagenix’ MetaRecon reverse engineers metadata information by examining the raw data contained in the source(s) rather than depending on the data dictionaries of the existing legacy systems (which are often incorrect). Other unique Metagenix approaches include an "open book" policy, which includes publishing product price lists on their web site and complete access to company officials, including CEO and President Greg Leman. According to Mr. Leman, "we’re pathologically honest".

data flow design  Reverse Engineers Data Into Information Metagenix Reverse Engineers Data Into Information M. Reed - February 15, 2001 Event Summary Metagenix, Inc. has designed its flagship product, MetaRecon to, as they put it, Decipher Your Data Genome . The product reverse engineers all of the metadata ( data about data ) from data sources and generates information that is very helpful to developers in designing specifications for a new data store, and assists greatly in preparing for cleansing and Read More

Four Critical Success Factors to Cleansing Data


Quality data in the supply chain is essential in when information is automated and shared with internal and external customers. Dirty data is a huge impediment to businesses. In this article, learn about the four critical success factors to clean data: 1- scope, 2- team, 3- process, and 4- technology.

data flow design  Success Factors to Cleansing Data Four Critical Success Factors to Cleansing Data If you receive errors when attempting to view this white paper, please install the latest version of Adobe Reader. Data Cleansing and Synchronization Services The pace with which companies are forced to operate and to compete globally has taxed exisitng systems and increased their inefficiencies. Source : PM ATLAS Business Group, LLC Resources Related to Critical Success Factors to Cleansing Data : Data Cleansing Read More

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 quality is low, and the short- and long-term benefits are great.

data flow design  Basics: Unscrubbed Data Is Poisonous Data Introduction A manufacturing company experienced continually increasing overhead costs in its purchasing and materials departments. It also began to see increased inventory levels and production line delays. A consulting firm was brought in to analyze the company's materials management processes and the level of competence of its materials and procurement staff. After mapping the entire process, from the creation of a bill of materials through post-sales Read More

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 environment. This article looks at issues in data quality and how they can be addressed.

data flow design  Data: The Importance of Data Quality in Business Intelligence Originally Published - October 20, 2008 The zeal to get as much business data to the user as soon as possible often prevails over the establishment of processes that control the quality of data. Low data quality standards can lead to bad business decisions and missed opportunities. Even with a data warehouse that is well designed and equipped with the best tools for business intelligence (BI), users will encounter inefficiency and frustration Read More

Revamping Data Management: Big Data Proves Catalyst to Updating Data Management Strategies


Data management plays a key role in helping organizations make strategic sense of their data and how to best use it. Organizations with data management maturity have ushered in clear data goals, but many obstacles persist. This white paper reports survey results that help to establish a clear picture of how organizations are capitalizing on data management today, as well as what challenges and opportunities remain.

data flow design  Data Management: Big Data Proves Catalyst to Updating Data Management Strategies Data management plays a key role in helping organizations make strategic sense of their data and how to best use it. Organizations with data management maturity have ushered in clear data goals, but many obstacles persist. This white paper reports survey results that help to establish a clear picture of how organizations are capitalizing on data management today, as well as what challenges and opportunities remain. Read More

Appliance Power: Crunching Data Warehousing Workloads Faster and Cheaper than Ever


Appliances are taking up permanent residence in the data warehouse (DW). The reason: they are preconfigured, support quick deployment, and accelerate online analytical processing (OLAP) queries against large, multidimensional data sets. Discover the core criteria you should use to evaluate DW appliances, including performance, functionality, flexibility, scalability, manageability, integration, and extensibility.

data flow design  Power: Crunching Data Warehousing Workloads Faster and Cheaper than Ever Appliances are taking up permanent residence in the data warehouse (DW). The reason: they are preconfigured, support quick deployment, and accelerate online analytical processing (OLAP) queries against large, multidimensional data sets. Discover the core criteria you should use to evaluate DW appliances, including performance, functionality, flexibility, scalability, manageability, integration, and extensibility. Read More