X
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 solutions by funtionality, so that you can make accurate and informed software purchasing decisions.
Compare Now
 

 etl data warehouse


Halo Source: High performance data warehouse, ETL and OLAP Cube


etl data warehouse  High performance data warehouse, ETL and OLAP Cube

Read More


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. 

Evaluate Now

Documents related to » etl data warehouse

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  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 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  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

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.

etl data warehouse  extract, transform, and load (ETL) process in a data warehousing system extracts records from data source(s), transforms them using rules to convert data into a form that is suitable for reporting and analysis, and finally loads the transformed records into the destination (typically a data warehouse or data mart). Data cleansing is an integral part of the transformation process and enforces business and schema rules on each record and field. Data cleansing involves the application of quality screens 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  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

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.

etl data warehouse  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

Big Data Comes of Age: Shifting to a Real-time Data Platform


New data sources are fueling innovation while stretching the limitations of traditional data management strategies and structures. Data warehouses are giving way to purpose-built platforms more capable of meeting the real-time needs of more demanding end users and the opportunities presented by big data. Read this white paper to learn more about the significant strategy shifts underway to transform traditional data ecosystems by creating a unified view of the data terrain necessary to support big data and the real-time needs of innovative companies.

etl data warehouse  Data Comes of Age: Shifting to a Real-time Data Platform New data sources are fueling innovation while stretching the limitations of traditional data management strategies and structures. Data warehouses are giving way to purpose-built platforms more capable of meeting the real-time needs of more demanding end users and the opportunities presented by big data. Read this white paper to learn more about the significant strategy shifts underway to transform traditional data ecosystems by creating a Read More

Understanding the PCI Data Security Standard


The payment card industry data security standard (PCI DSS) defines a comprehensive set of requirements to enhance and enforce payment account data security in a proactive rather than passive way. These include security management, policies, procedures, network architectures, software design, and other protective measures. Get a better understanding of the PCC DSS and learn the costs and benefits of compliance.

etl data warehouse  the PCI Data Security Standard MessageLabs Hosted Web Security and Content Filtering service operates at the Internet level, intercepting viruses, and spyware. Source : MessageLabs | Now part of Symantec Resources Related to Understanding the PCI Data Security Standard : Payment Card Industry Data Security Standard (PCI DSS) (Wikipedia) Understanding the PCI Data Security Standard Data Security is also known as : Data Security Architecture , Data Security Articles , Data Security Audit , Read More

Implementing Energy-Efficient Data Centers


But in the white paper implementing energy-efficient data centers, you'll learn how to save money by using less electricitywhether your data cente...

etl data warehouse  Energy-Efficient Data Centers Did you realize that your data center(s) may be costing you money by wasting electricity ? Or that there are at least 10 different strategies you can employ to dramatically cut data center energy consumption ? The fact is, most data centers are not designed with energy efficiency in mind. But in the white paper Implementing Energy-efficient Data Centers , you'll learn how to save money by using less electricity—whether your data centers are still in the design Read More

Warehouse Advantage


pdg group model 1270

etl data warehouse   Read More

Infor SCM Warehouse Management Provia


Infor SCM Warehouse Management is a modern extended-warehouse-management supply chain solution that provides business agility by automating fulfillment and distribution processes. Its core capabilities include inventory management, work and task management, and labor forecasting. The solution also supports capabilities such as slotting yard management voice-directed distribution cross-docking costing multiple inventory ownership value-added services billing and invoicing for third-party logistics (3PL) providers radio frequency identification (RFID) Infor SCM Warehouse Management is based on a modern Java 2 Platform Enterprise Edition (J2EE), zero-footprint, stateless architecture that is wide area network (WAN)-deployable with no client administration. This allows organizations to personalize radio frequency (RF) and terminal server environments to business and user needs, and provides a scalable architecture for centralized and decentralized support. Infor SCM Warehouse Management has been deployed in more than 20 countries, in multiple languages, and is available in an enterprise or business edition.

etl data warehouse   Read More

A Roadmap to Data Migration Success


Many large business initiatives and information technology (IT) projects depend upon the successful migration of data—from a legacy source, or multiple sources, to a new target database. Effective planning and scoping can help you address the associated challenges and minimize risk for errors. This paper provides insights into what issues are unique to data migration projects and to offer advice on how to best approach them.

etl data warehouse  Roadmap to Data Migration Success Many large business initiatives and information technology (IT) projects depend upon the successful migration of data—from a legacy source, or multiple sources, to a new target database. Effective planning and scoping can help you address the associated challenges and minimize risk for errors. This paper provides insights into what issues are unique to data migration projects and to offer advice on how to best approach them. Read More

Developing a Universal Approach to Cleansing Customer and Product Data


Data quality has always been an important issue for companies, and today it’s even more so. But are you up-to-date on current industry problems concerning data quality? Do you know how to address quality problems with customer, product, and other types of corporate data? Discover how data cleansing tools help improve data constancy and accuracy, and find out why you need an enterprise-wide approach to data management.

etl data warehouse  component includes a batch-oriented ETL product (BusinessObjects Data Integrator), an enterprise information integration tool for on-demand data access to a variety of data sources (BusinessObjects Data Federator), and a set of packaged data integration solutions (BusinessObjects Rapid Marts™) for enterprise applications such as Oracle, PeopleSoft, and Siebel. Data quality -a component for the profiling, cleansing, enhancement, matching, consolidation, and monitoring of data (BusinessObjects Data 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.

etl data warehouse  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 Read More