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Software Functionality Revealed in Detail
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 etl data warehouse architecture

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 » etl data warehouse architecture

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.

etl data warehouse architecture  via another set of ETL processes. It is in this layer data begins to take shape and it is not uncommon to have some end-user application access data from this layer especially if they are time sensitive, as data will become available here before it is transformed into the dimension / performance layer. Traditionally this layer is implemented in the Third Normal Form (3NF). Optimizing 3NF Optimizing a 3NF schema in Oracle requires the three Ps – Power, Partitioning and Parallel Execution. Power means Read More

Unlocking Hidden Value from Investments in SAP NetWeaver Business Warehouse


Extending the capabilities and value of SAP NetWeaver Business Warehouse is a concern for users. To improve data use and fact-based decision making, and reduce stranded spreadsheets, SAP users can choose a business intelligence (BI) software solution such as IBM Cognos 8, with budgeting, planning, and forecasting functions. Find out more about how you can improve your business performance management content with BI.

etl data warehouse architecture  Warehousing Best Practices | ETL in Data Warehousing | Data Warehousing White Papers | Data Warehousing Methodology | Data Warehousing Strategy | New Trends in Data Warehousing and Data Analysis | Data Management | Business Intelligence Software | IBM Cognos 8 Solutions | What is Business Information Warehouse | Omprehensive Business Intelligence Product | IBM Data Warehouse | Data Warehouse Performance | Data Business | Components & Tools of SAP Netweaver | Read More

The Necessity of Data Warehousing


An explanation of the origins of data warehousing and why it is a crucial technology that allows businesses to gain competitive advantage. Issues regarding technology selection and access to historical 'legacy' data are also discussed.

etl data warehouse architecture  issue is whether the ETL tool moves all the data through its own engine on the way to the target, or can be a proxy and move the data directly from the source to the target. Selection of the business intelligence tool(s) requires decisions such as: Will multi-dimensional analysis be necessary, or does the organization need only generalized queries? Not all warehouse implementations require sophisticated analysis techniques such as data mining (statistical analysis to discover trends in the data), data v 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.

etl data warehouse architecture  data warehouse design. All ETL data warehouse processes were originally designed to be executed in batch mode, during previously scheduled downtimes. All operational data from distinct sources (e.g. ERP systems) was extracted, cleansed under a stage repository, and loaded into the data warehouse over long periods of time, mostly at night. These processes can take minutes or hours, depending on the volume of data being uploaded to the data warehouse. With the pressure to load more recent data into the Read More

SAS/Warehouse 2.0 Goes Live


SAS Institute has announced the production availability of SAS/Warehouse Administrator software, Version 2.0. This new version provides IT the ability to proactively publish data warehouse information and track its usage, plus aggressively manage the process of change in the data warehouse.

etl data warehouse architecture  extraction, transformation and loading (ETL) processes, Nauta said. By tracking the usage of information in the warehouse, IT staff can identify and remove data that is not being used. Removing unnecessary data makes the warehouse more efficient and maximizes hardware investments. Market Impact Publish/Subscribe metaphors are becoming much more common in the data warehouse arena. The ability for users to subscribe (request information on a regular basis), and for the server to publish ( push ) that Read More

Warehouse Management Systems by the Numbers


When it comes to warehouse management systems (WMS), the stats are both shocking and thought-provoking. And although you don't see these stats in the marketing brochures of WMS vendors, you need to think about them before you purchase a WMS.

etl data warehouse architecture  Management Systems by the Numbers Warehouse Management Systems by the Numbers Featured Author - Ren Jones - September 22, 2006 Warehouses are built around numbers—from the facility''s square footage, to how many rows of racking it takes to stock the number of stock-keeping units (SKUs), all the way to the amount of orders processed through a facility in a day. This article takes the numbers associated with warehouse management systems (WMS) you don''t see in the marketing brochures or Read More

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 to the challenges of protecting distributed business data by establishing a private cloud/enterprise cloud. Learn which best practices can ensure business continuity throughout an organization with a distributed information technology (IT) infrastructure.

etl data warehouse architecture  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 to the challenges of protecting distributed business data by establishing a private cloud/enterprise cloud. Learn which best practices can ensure business continuity throughout an organization with a distributed information Read More

AlwaysUp Architecture


“Downtime” is a word no one wants to hear. Downtime costs money and resources—and possibly customers—while you redeploy code, configure applications, add data to failed systems, and replace now-useless hardware.

This document from Peak Hosting looks at the company’s AlwaysUp Architecture.

etl data warehouse architecture  Architecture “Downtime” is a word no one wants to hear. Downtime costs money and resources—and possibly customers—while you redeploy code, configure applications, add data to failed systems, and replace now-useless hardware. This document from Peak Hosting looks at the company’s AlwaysUp Architecture. 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.

etl data warehouse architecture  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

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.

etl data warehouse architecture  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

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?

etl data warehouse architecture  Warehouse Builder: Better Late than Never? Event Summary REDWOOD SHORES, Calif., Mar. 6, 2000 - Oracle announced the immediate availability of Oracle Warehouse Builder, 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 Read More

Six Steps to Manage Data Quality with SQL Server Integration Services


Without data that is reliable, accurate, and updated, organizations can’t confidently distribute that data across the enterprise, leading to bad business decisions. Faulty data also hinders the successful integration of data from a variety of data sources. But with a sound data quality methodology in place, you can integrate data while improving its quality and facilitate a master data management application—at low cost.

etl data warehouse architecture  Steps to Manage Data Quality with SQL Server Integration Services Melissa Data''s Data Quality Suite operates like a data quality firewall '' instantly verifying, cleaning, and standardizing your contact data at point of entry, before it enters your database. Source : Melissa Data Resources Related to Six Steps to Manage Data Quality with SQL Server Integration Services : Data quality (Wikipedia) Six Steps to Manage Data Quality with SQL Server Integration Services Data Quality is also known as : Busin Read More

The Importance of a Single Product for Data Quality and Data Integration


Companies are fighting a constant battle to integrate business data and content while managing data quality. Data quality serves as the foundation for business intelligence (BI), enterprise resource planning (ERP), and customer relationship management (CRM) projects. Learn more about software that unifies leading data quality and integration solutions—helping your organization to move, transform, and improve its data.

etl data warehouse architecture  Importance of a Single Product for Data Quality and Data Integration Companies are fighting a constant battle to integrate business data and content while managing data quality. Data quality serves as the foundation for business intelligence (BI), enterprise resource planning (ERP), and customer relationship management (CRM) projects. Learn more about software that unifies leading data quality and integration solutions—helping your organization to move, transform, and improve its data. Read More

IntegrateIT ERP 123 V7.2.561 for Warehouse Management System (WMS) Product Certification Report


Technology Evaluation Centers (TEC) is pleased to announce that IntegrateIT product ERP 123 is now TEC Certified for online evaluation of warehouse management system (WMS) solutions in TEC's Supply Chain Management (SCM) Evaluation Center. The certification seal is a valuable indicator for organizations relying on the integrity of TEC research for assistance with their software selection projects. Download this report for product highlights, competitive analysis, product analysis, and in-depth analyst commentary.

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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.

etl data warehouse architecture  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