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Software Functionality Revealed in Detail
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 implementing data warehouse 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

Warehouse Management Systems (WMS)

A warehouse management system (WMS) should provide database and user-level tools in order for a company to optimize its storage facilities while at the same time providing user level task direction and activity support. The WMS should enable warehouse operators to optimize pick, put-away, and replenishment functions by employing powerful system logic to select the best locations and sequences. 

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Documents related to » implementing data warehouse etl

Best Practices for a Data Warehouse on Oracle Database 11g


Companies are recognizing the value of an enterprise data warehouse (EDW) that provides a single 360-degree view of the business. But to ensure that your EDW performs and scales well, you need to get three things right: the hardware configuration, the data model, and the data loading process. Learn how designing these three things correctly can help you scale your EDW without constantly tuning or tweaking the system.

implementing data warehouse etl  Data Warehouse Info | Implementing Data Warehouse | Data Warehouse Process | Implementing Real Time Data Warehousing | Data Warehouse System Complete | Data Warehouse EDW | Data Warehouse Architecture EDW | Data Warehouse Concepts EDW | Data Warehousing Information Center EDW | Data Integration Paper EDW | Data Warehouse Software EDW | Data Warehousing Analysis EDW | Data Warehouse Community EDW | Data Warehouse Automation EDW | Perspectives on Data Warehousing EDW | Data Warehousing OLAP EDW | Resource 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.

implementing data warehouse etl  the technical difficulties of implementing a true real-time data warehouse, there are some advantages. It shortens information delivery times. It improves integration throughout the organization. It eases the analysis of future trends. Basic Principles to Consider With the growing popularity and increasing implementation of real-time data warehouses, it is important to consider some basic principles when considering a real-time data warehouse implementation. Data on Time, at the Right Time . The data 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.

implementing data warehouse etl  the topics related to implementing a data warehouse solution. Included were data profiling; data transformation; data cleansing; source and target mapping; data cleansing and transformation; and extract, transform, and load (ETL) development. It is important not to underestimate the importance of data integration, as the way data is integrated into a data warehouse or BI solution is the essence of that system. If a scorecard is developed to measure an organization''s sales metrics and the source data is Read More

A Road Map to Data Migration Success


Many significant business initiatives and large IT projects depend upon a successful data migration. But when migrated data is transformed for new uses, project teams encounter some very specific management and technical challenges. Minimizing the risk of these tricky migrations requires effective planning and scoping. Read up on the issues unique to data migration projects, and find out how to best approach them.

implementing data warehouse etl  processes that they are implementing. Allow time in your planning for changes to the mapping, business rules, and re-loads. It is not uncommon for there to be confusion during beta testing and implementation as to where errors originate. It''s all too easy for bad data to be blamed for every test error. What can you do as part of your planning to avoid this? Implement the migration with as much metadata and reconciliation as possible. Not only are you ensuring the integrity of your data, you are Read More

More Data is Going to the Cleaners


WESTBORO, Mass., November 29, 1999 - Ardent Software, Inc. (Nasdaq: ARDT) today announced a strategic partnership with Firstlogic, Inc., the developer of i.d.Centric data quality software that helps companies cleanse and consolidate data in database marketing, data warehousing, and e-business applications. Under the partnership agreement Firstlogic will develop and support a link between its customer data quality tools and Ardent's DataStage Suite.

implementing data warehouse etl  Ardent''s DataStage Suite. Organizations implementing complex database marketing programs and e-business strategies depend on extensive data quality assurance. Together Ardent and Firstlogic are meeting this market need, said Mikael Wipperfeld, vice president of data warehouse marketing at Ardent Software. This partnership allows our joint customers to take advantage of Firstogic''s address verification, name parsing and extensive matching and consolidation capabilities inside the DataStage suite, the Read More

The Fast Path to Big Data


Today, most people acknowledge that big data is more than a fad and is a proven model for leveraging existing information sources to make smarter, more immediate decisions that result in better business outcomes. Big data has already been put in use by companies across vertical market segments to improve top- and bottom-line performance. As unstructured data becomes a pervasive source of business intelligence, big data will continue to play a more strategic role in enterprise information technology (IT). Companies that recognize this reality—and that act on it in a technologically, operationally, and economically optimized way—will gain sustainable competitive advantages.

implementing data warehouse etl  Fast Path to Big Data Today, most people acknowledge that big data is more than a fad and is a proven model for leveraging existing information sources to make smarter, more immediate decisions that result in better business outcomes. Big data has already been put in use by companies across vertical market segments to improve top- and bottom-line performance. As unstructured data becomes a pervasive source of business intelligence, big data will continue to play a more strategic role in enterprise Read More

Cost-justifying Warehouse Management Technologies in Small and Midsized Warehouses


The warehouse management system (WMS) concept has matured into a collection of time-tested technologies that reduce inventory costs and increase overall inventory management efficiencies. By implementing WMS technology, organizations can achieve a higher return on their software dollars and provide better service to their customers. A WMS can provide organizations with tangible benefits that improve warehouse operations without adding headcount.

implementing data warehouse etl  without adding headcount. By implementing a WMS, a company achieves a number of significant benefits that include: Reduced picking/shipping errors Improved inventory count accuracy Increased employee productivity Elimination of most warehouse paperwork Improved space utilization Reduction of physical inventories Better workload control Improved labor management and reporting Better support of customer EDI requirements Ability to better prioritize warehouse activities for preferred customers In this Read More

Implementing Business Process Management (BPM) to Drive Profitable Sales


Find out how this company succeeded in Implementing BPM to Drive Profitable Sales.

implementing data warehouse etl  this company succeeded in Implementing BPM to Drive Profitable Sales . You’ll learn how a holistic, process-driven approach resulted in: renewal of the sales funnel process optimization of resources more efficient usage of time standardization of the sales process Discover how your company can improve its business processes to increase sales and reduce costs. Download your PDF copy of   Implementing BPM to Drive Profitable Sales today.   For assistance, please contact customer service. Hours: 8:00 AM Read More

Simulation In The Warehouse


Simulation can remedy one time and ongoing problems in the warehouse. Learn about the technology of computer stimulation and how it can benefit senior management in the logistics, distribution, and warehousing industries. This paper will describe the benefits of simulation as an analytical tool and the industrial lessons learned from failed simulation projects.

implementing data warehouse etl  storage,catalyst,simulation,management,logistic Read More

The Value of Big Data


As the use of big data grows, the need for data management will also grow. Many organizations already struggle to manage existing data. Big data adds complexity, which will only increase the challenge. This white paper looks at what big data is, the value of big data, and new data management capabilities and processes, required to capture the promised long-term value.

implementing data warehouse etl  Value of Big Data As the use of big data grows, the need for data management will also grow. Many organizations already struggle to manage existing data. Big data adds complexity, which will only increase the challenge. This white paper looks at what big data is, the value of big data, and new data management capabilities and processes, required to capture the promised long-term value. Read More

Big Data, Little Data, and Everything in Between—IBM SPSS Solutions Help You Bring Analytics to Everyone


Regardless of the type or scale of business data your users need to harness and analyze, they need a straightforward, visual solution that is easy to use on the front end and highly scalable on the back end. Fortunately, IBM SPSS solutions provide just such an ecosystem that can make different kinds of data stores—from Hadoop to those proverbial spreadsheets—useful sources of business insight and decision support.

implementing data warehouse etl  Data, Little Data, and Everything in Between—IBM SPSS Solutions Help You Bring Analytics to Everyone Regardless of the type or scale of business data your users need to harness and analyze, they need a straightforward, visual solution that is easy to use on the front end and highly scalable on the back end. Fortunately, IBM SPSS solutions provide just such an ecosystem that can make different kinds of data stores—from Hadoop to those proverbial spreadsheets—useful sources of business insight and Read More

Data Mining with MicroStrategy: Using the BI Platform to Distribute Data Mining and Predictive Analytics to the Masses


Data mining and predictive analysis applications can help you make knowledge-driven decisions and improve efficiency. But the user adoption of these tools has been slow due to their lack of business intelligence (BI) functionality, proactive information distribution, robust security, and other necessities. Now there’s an integrated enterprise BI system that can deliver data mining and predictive analysis. Learn more.

implementing data warehouse etl  Mining with MicroStrategy: Using the BI Platform to Distribute Data Mining and Predictive Analytics to the Masses Data mining and predictive analysis applications can help you make knowledge-driven decisions and improve efficiency. But the user adoption of these tools has been slow due to their lack of business intelligence (BI) functionality, proactive information distribution, robust security, and other necessities. Now there’s an integrated enterprise BI system that can deliver data mining and pre Read More

MSI Data


There are currently no details available for this vendor. However, we are working to update this vendor’s information in our database as soon as possible. Please check back again.

implementing data warehouse etl  Data Read More

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.

implementing data warehouse etl  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 Read More

Increasing Sales and Reducing Costs across the Supply Chain-Focusing on Data Quality and Master Data Management


Nearly half of all US companies have serious data quality issues. The problem is that most are not thinking about their business data as being valuable. But in reality data has become—in some cases—just as valuable as inventory. The solution to most organizational data challenges today is to combine a strong data quality program with a master data management (MDM) program, helping businesses leverage data as an asset.

implementing data warehouse etl  Sales and Reducing Costs across the Supply Chain-Focusing on Data Quality and Master Data Management Nearly half of all US companies have serious data quality issues. The problem is that most are not thinking about their business data as being valuable. But in reality data has become—in some cases—just as valuable as inventory. The solution to most organizational data challenges today is to combine a strong data quality program with a master data management (MDM) program, helping businesses Read More