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Software Functionality Revealed in Detail
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 definition of data warehousing etl

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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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 describes the process of defining, populating, and using a data warehouse. Creating, populating, and querying a data warehouse typically carries an extremely high price tag, but the return on investment can be substantial. Over 95% of the Fortune 1000 have a data warehouse initiative underway in some form.

definition of data warehousing etl  Definition of Data Warehousing Biographical Information Bill Inmon Bill Inmon is universally recognized as the father of the data warehouse. He has over 26 years of database technology management experience and data warehouse design expertise, and has published 36 books and more than 350 articles in major computer journals. His books have been translated into nine languages. He is known globally for his seminars on developing data warehouses and has been a keynote speaker for every major computing Read More

Optimizing Gross Margin over Continously Cleansed Data


Imperfect product data can erode your gross margin, frustrate both your customers and your employees, and slow new sales opportunities. The proven safeguards are automated data cleansing, systematic management of data processes, and margin optimization. Real dollars can be reclaimed in the supply chain by making certain that every byte of product information is accurate and synchronized, internally and externally.

definition of data warehousing etl  Cost Data | Product Definition Data | Product Life Cycle Data | Product Performance Data | Product Pricing Data | Product Reference Data | Product Review Data | Product Sales Data | Products Reference Data | Quality Data Products | Resource Data Products | Source Data Products | Technical Product Data | True Data Products | Virtual Product Data | World Data Product | PMPO Product Data | PMPO Product Data Analyst | PMPO Product Data Base | PMPO Product Data Feed | PMPO Product Data File | PMPO Product Read More

A One-stop Event for Business Intelligence and Data Warehousing Information


The Data Warehousing Institute (TDWI) hosts quarterly World Conferences to help organizations involved in data warehousing, business intelligence, and performance management. These conferences supply a wealth of information aimed at improving organizational decision-making, optimizing performance, and achieving business objectives.

definition of data warehousing etl  included performance management, the definition and delivery of business metrics, data visualization, and the deployment and use of technology solutions. Solutions discussed included online analytical processing (OLAP), dashboards, scorecards, and data mining, as well as analytic applications. This focus allows organizations to gain insight into areas within BI and the different aspects of insight that analytics can provide. Organizations that require a subset of BI can identify how their needs can be Read More

Access to Critical Business Intelligence: Challenging Data Warehouses?


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definition of data warehousing etl  but a DW, by definition, is a copy of the original data records. DWs are constantly being shifted, updated, or consolidated, and they combine data from multiple systems, each with different business rules. On the contrary, Vanguard''s Direct Access pulls information directly from the transaction systems—the real systems of record—so that the question of what version of the data is reported becomes obsolete. The issue is also whether there is a point of integrating a large amount of data in a DW when Read More

Best Practices for a Data Warehouse on Oracle Database 11g


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Soaring across the Regions: A View of the Impact of the Internet on Business


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definition of data warehousing etl  across the Regions: A View of the Impact of the Internet on Business The Internet offers companies the opportunity to present a commercial image independent of size and location. With this and the Internet’s ability to extend a business’s reach, it is valuable to know precisely what various Internet service providers (ISPs) offer before buying. This includes evaluating service level and support capabilities and understanding how these vary throughout the United Kingdom (UK). Find out more. Read More

Addressing the Complexities of Remote Data Protection


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Maximize the Green Efficiency of Multi-Site National Rollouts of Technology


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definition of data warehousing etl  the Green Efficiency of Multi-Site National Rollouts of Technology The service industry consumes millions of gallons of fuel and expends trillions of pounds of carbon monoxide each year as trucks roll to installation and service locations. Eliminating unnecessary travel is one way service companies can help protect the environment, and meet environmental compliance requirements. Discover a methodology that can help you reduce your fleet’s fuel consumption and carbon monoxide emissions. Read More

Never Was A Story Of More Woe Than This Of RJR And Nabisco


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Considerations for Owning versus Outsourcing Data Center Physical Infrastructure


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definition of data warehousing etl  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, Read More

Streaming Data and the Fast Data Stack


Big data is data at rest; fast data is streaming data, or data in motion. A stack is emerging across verticals and industries for building applications that process these high velocity streams of data. This new stack, the fast data stack, has a unique purpose: to grab real-time data and output recommendations, decisions, and analyses in milliseconds.

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Companies recognize the need to integrate big data into their real-time analytics and operations, but this poses a lot of technical and resource challenges. Meanwhile, those organizations that have operational data stores (ODSs) in place find that, while useful, they are expensive to scale. The ODS gives real-time visibility into operational data. While more cost-effective than a data warehouse, it uses outdated scaling technology, and performance upgrades require very specialized hardware. Plus, ODSs just can't handle the volume of data that has become a matter of fact for businesses today.

This white paper discusses the concept of the operational data lake, and its potential as an on-ramp to big data by upgrading outdated ODSs. Companies that are building a use case for big data, or those considering an upgrade to their ODS, may benefit from this stepping stone. With a Hadoop relational database management system (RDBMS), companies can expand their big data practices at their own pace.

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