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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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 data warehouse system complete 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 » data warehouse system complete 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.

data warehouse system complete etl  Practices for a Data Warehouse on Oracle Database 11g Best Practices for a Data Warehouse on Oracle Database 11g If you receive errors when attempting to view this white paper, please install the latest version of Adobe Reader. Oracle has been helping customers like you manage your business systems and information with reliable, secure, and integrated technologies. Source : Oracle Resources Related to Data Warehouse : Data Warehouse (Wikipedia) Best Practices for a Data Warehouse on Oracle Database 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.

data warehouse system complete etl  (ETL) code for a data warehouse faces a new set of challenges when migrating data to a live, operational system. Although a 2% error rate may be acceptable for aggregate reporting, it is not acceptable for customer contact data—in this example, we would fail to recognize one out of 50 customers when they call! Many significant business initiatives and large IT projects depend upon a successful data migration. Your goal is to minimize as much of your risk as possible through effective planning and Read More

Oracle Warehouse Builder: Better Late than Never?


Close to a year behind schedule, Oracle released Warehouse Builder to the market. Oracle, in an interesting contradiction in terms, has stated that the product is “already in production at nearly 20 beta sites.” But is it too little too late?

data warehouse system complete etl  an extensible and easy-to-use data warehouse design and deployment framework. As part of Oracle''s Intelligent WebHouse Initiative, Oracle Warehouse Builder automates much of the work that goes into creating a powerful, single data store for e-business analysis, specifically with its ability to integrate historical data with the massive, daily influxes of online data from web sites. The product, already in production at nearly 20 beta sites worldwide, is available for purchase tomorrow. The Oracle 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 warehouse system complete etl  Evolution of a Real-time Data Warehouse The Evolution of a Real-time Data Warehouse Jorge Garcia - December 23, 2009 Understanding Real-time Systems Today, real time computing is everywhere, from customer information control systems (CICSs) to real-time data warehouse systems. Real-time systems have the ability to respond to user actions in a very short period of time. This computing behavior gives real-time systems special features such as instant interaction: users request information from the system an Read More

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.

data warehouse system complete etl  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 association. Before founding Pine Cone Systems, Bill was a co-founder of Prism Solutions, Inc. Ralph Kimball Ralph Kimball was co-inventor of the Xerox Star workstation, the first Read More

Don't Be Overwhelmed by Big Data


Big Data. The consumer packaged goods (CPG) industry is abuzz with those two words. And while it’s understandable that the CPG world is excited by the prospect of more data that can be used to better understand the who, what, why, and when of consumer purchasing behavior, it’s critical CPG organizations pause and ask themselves, “Are we providing retail and executive team members with “quality” data, and is the data getting to the right people at the right time? Big Data can be a Big Deal - read this white paper for some useful tips on ensuring secure, quality data acquisition and management.

data warehouse system complete etl  Be Overwhelmed by Big Data Big Data. The consumer packaged goods (CPG) industry is abuzz with those two words. And while it’s understandable that the CPG world is excited by the prospect of more data that can be used to better understand the who, what, why, and when of consumer purchasing behavior, it’s critical CPG organizations pause and ask themselves, “Are we providing retail and executive team members with “quality” data, and is the data getting to the right people at the right time? Big Read More

Linked Enterprise Data: Data at the heart of the company


The data silos of today's business information systems (IS) applications, and the pressure from the current economic climate, globalization, and the Internet make it critical for companies to learn how to manage and extract value from their data. Linked enterprise data (LED) combines the benefits of business intelligence (BI), master data management (MDM), service-oriented architecture (SOA), and search engines to create links among existing data, break down data walls, provide an open, secure, and long-term technological environment, and reduce complexity—read this white paper to find out how.

data warehouse system complete etl  Enterprise Data: Data at the heart of the company The data silos of today''s business information systems (IS) applications, and the pressure from the current economic climate, globalization, and the Internet make it critical for companies to learn how to manage and extract value from their data. Linked enterprise data (LED) combines the benefits of business intelligence (BI), master data management (MDM), service-oriented architecture (SOA), and search engines to create links among existing data, 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.

data warehouse system complete 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

Protecting Critical Data


The first step in developing a tiered data storage strategy is to examine the types of information you store and the time required to restore the different data classes to full operation in the event of a disaster. Learn how in this white paper from Stonefly.

data warehouse system complete etl  Critical Data The first step in developing a tiered data storage strategy is to examine the types of information you store and the time required to restore the different data classes to full operation in the event of a disaster. Learn how in this white paper from Stonefly. Read More

Re-think Data Integration: Delivering Agile BI Systems with Data Virtualization


Read this white paper to learn about a lean form of on-demand data integration technology called data virtualization. Deploying data virtualization results in business intelligence (BI) systems with simpler and more agile architectures that can confront the new challenges much more easily.

All the key concepts of data virtualization are described, including logical tables, importing data sources, data security, caching, and query optimization. Examples are given of application areas of data virtualization for BI, such as virtual data marts, big data analytics, extended data warehouse, and offloading cold data.

data warehouse system complete 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

Data Quality Trends and Adoption


While much of the interest in data quality (DQ) solutions had focused on avoiding failure of data management-related initiatives, organizations now look to DQ efforts to improve operational efficiencies, reduce wasted costs, optimize critical business processes, provide data transparency, and improve customer experiences. Read what DQ purchase and usage trends across UK and US companies reveal about DQ goals and drivers.

data warehouse system complete etl  of the interest in data quality (DQ) solutions had focused on avoiding failure of data management-related initiatives, organizations now look to DQ efforts to improve operational efficiencies, reduce wasted costs, optimize critical business processes, provide data transparency, and improve customer experiences. Read what DQ purchase and usage trends across UK and US companies reveal about DQ goals and drivers. Read More

The Quadstone System


Quadstone sells three products components within the Quadstone System: Decisionhouse, Transactionhouse, and Actionhouse. Decisionhouse is the flagship product—it combines customer data discovery with automated predictive modeling. Transactionhouse is used to gather data from various sources (relational databases, operational data stores, log, and flat files) into the Quadstone System and perform the necessary data transformations in order to create a single customer view. Actionhouse is used to allow the reuse of the results of the analytical process (selections, rules, models, scores) within operational enviornments such as marketing automation packages, call center systems or ecommerce systems.  

data warehouse system complete etl  flagship product—it combines customer data discovery with automated predictive modeling. Transactionhouse is used to gather data from various sources (relational databases, operational data stores, log, and flat files) into the Quadstone System and perform the necessary data transformations in order to create a single customer view. Actionhouse is used to allow the reuse of the results of the analytical process (selections, rules, models, scores) within operational enviornments such as marketing Read More

Five Standard Features Any VoIP System Should Have


Here's a guide to quickly fill you in on the Five Standard Features Any VoIP System Should Have.

data warehouse system complete etl  standard features voip system,standard,features,voip,system,features voip system,standard voip system,standard features system,standard features voip. Read More

Big Data: Operationalizing the Buzz


Integrating big data initiatives into the fabric of everyday business operations is growing in importance. The types of projects being implemented overwhelmingly favor operational analytics. Operational analytics workloads are the integration of advanced analytics such as customer segmentation, predictive analytics, and graph analysis into operational workflows to provide real-time enhancements to business processes. Read this report to learn more.

data warehouse system complete etl  the Buzz Integrating big data initiatives into the fabric of everyday business operations is growing in importance. The types of projects being implemented overwhelmingly favor operational analytics. Operational analytics workloads are the integration of advanced analytics such as customer segmentation, predictive analytics, and graph analysis into operational workflows to provide real-time enhancements to business processes. Read this report to learn more. Read More

Flexible Customer Data Integration Solution Adapts to Your Business Needs


Siperian's master data management and customer data integration (CDI) solutions allow organizations to consolidate, manage, and customize customer-related data. The type of CDI hub implemented depends on the CDI environment's maturity, requirements, and alignment with an organization's internal processes.

data warehouse system complete etl  Customer Data Integration Solution Adapts to Your Business Needs Customer data integration (CDI) has become one of the buzzwords within the master data management (MDM) industry. Although the concept of creating a single organizational view of the customer is noble and desirable, its value should also be justified by organizations. To implement a customer data hub that only creates a centralized view of an organization''s customer-related data does not affect a company''s bottom line, unless Read More