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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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 implementing data warehouse olap

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 olap

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 olap  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

Business Intelligence Success, Lessons Learned


Is business intelligence (BI) an application that pays off? We have all heard mixed results but a 2003 extensive study on on-line analytical processing (OLAP) states that BI usually pays off over 60 percent of the time , explains where the value is found, and describes what’s required to get the pay off.

implementing data warehouse olap  19 percent of companies implementing BI claim they have met or exceeded their business goals. Over 60 percent state they have at least largely met their goals. As always, soft benefits were more easily obtainable than hard benefits. A detailed look at the types of benefits reveals the following: Benefit % Companies Realizing Benefit Faster, more accurate reporting 81 Improved decision making 78 Improved customer service 56 Increased revenue 49 Savings in non-IT costs 50 IT savings 40 When the statistics Read More

Business Intelligence: Its Ins and Outs


In today's highly competitive business climate, the quality and timeliness of business information for an organization is not only a choice between profit and loss, it is a question of survival or bankruptcy. No business organization can deny the inevitable benefits of business intelligence.

implementing data warehouse olap  is a challenging job. Implementing BI is a costly and time consuming venture. If the wrong BI is implemented without good research and planning it could be a failure initiative. One very important point to be considered for selecting BI is there should be a close match between company''s requirements and vendors provided solutions. Companies seeking to implement a BI system should make sure they research their needs thoroughly. When looking for consultants, make sure they have detailed knowledge bases of Read More

Thinking Radically about Data Warehousing and Big Data: Interview with Roger Gaskell, CTO of Kognitio


Managing data—particularly in large numbers—still is and probably will be the number one priority for many organizations in the upcoming years. Many of the traditional ways to store and analyze large amounts of data are being replaced with new technologies and methodologies to manage the new volume, complexity, and analysis requirements. These include new ways of developing data warehousing, the

implementing data warehouse olap  is no overhead of implementing a data warehouse onsite, and there is no need for an information technology (IT) department to service, maintain, and support the database. Instead, organizations can focus on meeting their business goals, and not get bogged down with infrastructure issues. The challenge is always getting access to the data in the underlying source systems and deciding the type of cloud model that best suits the company. Is it ok to run analytic projects in the public cloud or would it be 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 olap  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

10 Errors to Avoid When Building a Data Center


In the white paper ten errors to avoid when commissioning a data center, find out which mistakes to avoid when you're going through the data center...

implementing data warehouse olap  Errors to Avoid When Building a Data Center Proper data center commissioning can help ensure the success of your data center design and build project. But it''s also a process that can go wrong in a number of different ways. In the white paper Ten Errors to Avoid when Commissioning a Data Center , find out which mistakes to avoid when you''re going through the data center commissioning process. From bringing in the commissioning agent too late into the process, to not identifying clear roles for 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.

implementing data warehouse olap  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? Read More

TCO Analysis of a Traditional Data Center vs. a Scalable, Containerized Data Center


Standardized, scalable, pre-assembled, and integrated data center facility power and cooling modules provide a total cost of ownership (TCO) savings of 30% compared with traditional, built-out data center power and cooling infrastructure. Avoiding overbuilt capacity and scaling the design over time contributes to a significant percentage of the overall savings. This white paper provides a quantitative TCO analysis of the two architectures, and illustrates the key drivers of both the capex and opex savings of the improved architecture.

implementing data warehouse olap  Analysis of a Traditional Data Center vs. a Scalable, Containerized Data Center Standardized, scalable, pre-assembled, and integrated data center facility power and cooling modules provide a total cost of ownership (TCO) savings of 30% compared with traditional, built-out data center power and cooling infrastructure. Avoiding overbuilt capacity and scaling the design over time contributes to a significant percentage of the overall savings. This white paper provides a quantitative TCO analysis of the Read More

Data Security Is Less Expensive than Your Next Liability Lawsuit: Best Practices in Application Data Security


Insecure data. Heavy fines due to non-compliance. Loss of customers and reputation. It adds up to a nightmare scenario that businesses want to avoid at all costs. However, this nightmare is preventable: knowledge base-driven data security solutions can be critical tools for enterprises wanting to secure not only their data—but also their status in the marketplace.

implementing data warehouse olap  Security Is Less Expensive than Your Next Liability Lawsuit: Best Practices in Application Data Security Insecure data. Heavy fines due to non-compliance. Loss of customers and reputation. It adds up to a nightmare scenario that businesses want to avoid at all costs. However, this nightmare is preventable: knowledge base-driven data security solutions can be critical tools for enterprises wanting to secure not only their data—but also their status in the marketplace. Read More

Overall Approach to Data Quality ROI


Data quality is an elusive subject that can defy measurement and yet be critical enough to derail any single IT project, strategic initiative, or even a company. Of the many benefits that can accrue from improving the data quality of an organization, companies must choose which to measure and how to get the return on investment (ROI)—in hard dollars. Read this paper to garner an overall approach to data quality ROI.

implementing data warehouse olap  Approach to Data Quality ROI Data quality is an elusive subject that can defy measurement and yet be critical enough to derail any single IT project, strategic initiative, or even a company. Of the many benefits that can accrue from improving the data quality of an organization, companies must choose which to measure and how to get the return on investment (ROI)—in hard dollars. Read this paper to garner an overall approach to data quality ROI. Read More

Data Migration Management: A Methodology to Sustaining Data Integrity for Going Live and Beyond


For many new system deployments, data migration is one of the last priorities. Data migration is often viewed as simply transferring data between systems, yet the business impact can be significant and detrimental to business continuity when proper data management is not applied. By embracing the five phases of a data migration management methodology outlined in this paper, you can deliver a new system with quality data.

implementing data warehouse olap  Migration Management: A Methodology to Sustaining Data Integrity for Going Live and Beyond For many new system deployments, data migration is one of the last priorities. Data migration is often viewed as simply transferring data between systems, yet the business impact can be significant and detrimental to business continuity when proper data management is not applied. By embracing the five phases of a data migration management methodology outlined in this paper, you can deliver a new system with Read More

Warehouse Management Systems: Pie in the Sky or Floating Bakery? Part One: Myths of the Warehouse Management Systems and Implementation


When searching for a warehouse management system (WMS), a number of myths surface. "Huge staff reductions", "quick and easy implementation", and "fast and big" returns on investment are common promises. These combined with the enticing "bells and whistles" of a system can ultimately turn an eager customer into a patient suffering from confusion or at the very least disorientation. Knowing the stories behind the myths and determining what your warehouse needs are can lead to a profitable investment.

implementing data warehouse olap  with several different companies'' implementing WMS systems and have yet to see someone properly implement a system in less than a year. Obviously these were larger warehouses, but this was even the case for ones that were 30,000 square feet with fifteen people. The problem was not that the systems were too complex, but that these companies had problems that needed to be addressed prior to going live on the system. Process failures are the result of a company''s culture and not the result of an archaic 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.

implementing data warehouse olap  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

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.

implementing data warehouse olap  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

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.

implementing data warehouse olap  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