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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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 difference between data warehouse


Data, Data Everywhere: A Special Report on Managing Information
The quantity of information in the world is soaring. Merely keeping up with, and storing new information is difficult enough. Analyzing it, to spot patterns and

difference between data warehouse  information can make a difference by enabling people to understand complex matters and find creative solutions. Valdis Krebs, a specialist in mapping social interactions, recalls being called in to help with a corporate project that was vastly over budget and behind schedule. He drew up an intricate network map of e-mail traffic that showed distinct clusters, revealing that the teams involved were not talking directly to each other but passing messages via managers. So the company changed its office

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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.

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 » difference between data warehouse

Teradata 2013 Partners Conference: Interview with Dan Graham, General Manager for Enterprise Systems, Teradata


BI Analyst Jorge Garcia interviews Dan Graham, General Manager for Enterprise Systems at Teradata, live on the show floor at the 2013 Teradata Partners Conference. Listen and find out how the Aster 6 SNAP framework handles data types that don’t fit easily into rows and columns, how having a JSON data type in the data warehouse helps companies deal with the internet of things, and why for a discovery platform there’s no real difference between beta and production.

difference between data warehouse  platform there’s no real difference between beta and production. Read More

SAP HANA-One Technology to Watch in 2012 (and Beyond)


Did you know that SAP HANA is much more than a high-speed analytic appliance? TEC principal analyst P.J. Jakovljevic reveals how HANA is a universal database that will enable companies to analyze large volumes of operational and transactional information in real time, from virtually any data source, and that will eventually deliver an entirely new class of applications that will change the way people think, work, plan, and operate.

difference between data warehouse  in one database? The difference between online analytical processing (OLAP) and online transactional processing (OLTP) is not only in their use, but also in the way the data is organized. OLAP is suitable for non-volatile data types, i.e., reporting and historical analysis of data that is stored in data warehouses (and periodically refreshed), whereas OLTP is for highly volatile (ever-changing) transactional systems. Although both OLAP and OLTP can be used universally, in theory at least, there are Read More

Bridging the Reality Gap Between Planning and Execution Part Two: The Manufacturers' Perspective


Manufacturers today need to react quickly in order to remain efficient and competitive, given that the biggest problem they face is that change is the only constant in manufacturing. For those who are lucky, only minor changes will happen between the "as planned" and "as executed" worlds.

difference between data warehouse  changes can determine the difference between profit and loss in manufacturing an order, or they can determine margin size in a manufacturing cycle or run. In addition to the above minor and major changes, manufacturers face a third and typically more powerful change to the business itself. Namely, to remain viable and prosper in today's ruthlessly competitive global markets, manufacturers must continually reinvigorate themselves and even occasionally reinvent themselves. Fundamental business changes Read More

Customer Data Integration: A Primer


Customer data integration (CDI) involves consolidation of customer information for a centralized view of the customer experience. Implementing CDI within a customer relationship management initiative can help provide organizations with a successful framework to manage data on a continuous basis.

difference between data warehouse  system can be the difference between success and failure in terms of leveraging an organization's customer relationship management (CRM) system. Since customers drive profitability, organizations need a way to provide their employees with a single view of the customer and to provide that customer with above-average customer service. Unfortunately, this is not always the case. Disparate applications such as billing and call center systems do not always feed into one another, and even when they do, lack of Read More

The Teradata Database and the Intelligent Expansion of the Data Warehouse


In 2002 Teradata launched the Teradata Active Enterprise Data Warehouse, becoming a key player in the data warehouse and business intelligence scene, a role that Teradata has maintained until now. Teradata mixes rigorous business and technical discipline with well-thought-out innovation in order to enable organizations to expand their analytical platforms and evolve their data initiatives. In this report TEC Senior BI analyst Jorge Garcia looks at the Teradata Data Warehouse in detail, including functionality, distinguishing characteristics, and Teradata's role in the competitive data warehouse space.

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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...

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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.

difference between data warehouse   Read More

New Data Protection Strategies


One of the greatest challenges facing organizations is the protection of corporate data. The issues complicating data protection are compounded by increased demand for data capacity and higher service levels. Often these demands are coupled with regulatory requirements and a shifting business environment. Learn about data protection strategies that can help organizations meet these demands while maintaining flat budgets.

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Considerations for Owning versus Outsourcing Data Center Physical Infrastructure


When faced with the decision of upgrading an existing data center, building new, or leasing space in a retail colocation data center, there are both quantitative and qualitative differences to consider. The 10-year TCO may favor upgrading or building over outsourcing; however, this paper demonstrates that the economics may be overwhelmed by a business’ sensitivity to cash flow, cash crossover point, deployment timeframe, data center life expectancy, regulatory requirements, and other strategic factors. This paper discusses how to assess these key factors to help make a sound decision.

difference between data warehouse  both quantitative and qualitative differences to consider. The 10-year TCO may favor upgrading or building over outsourcing; however, this paper demonstrates that the economics may be overwhelmed by a business’ sensitivity to cash flow, cash crossover point, deployment timeframe, data center life expectancy, regulatory requirements, and other strategic factors. This paper discusses how to assess these key factors to help make a sound decision. Read More

2012 Business Data Loss Survey results


This report on the Cibecs and IDG Connect 2012 business data loss survey uncovers the latest statistics and trends around enterprise data protection. Download the full results now.

difference between data warehouse  data protection,data backup,2012 data statistics,data loss,business data backup Read More

Data Visualization: When Data Speaks Business


For many organizations, data visualization is a practice that involves not only specific tools but also key techniques, procedures, and rules. The objective is to ensure the best use of existing tools for extending discovery, gaining knowledge, and improving the decision-making process at all organizational levels. This report considers the important effects of having good data visualization practices and analyzes some of the features, functions, and advantages of IBM Cognos Business Intelligence for improving the data visualization and data delivery process.

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Data Loss Prevention Best Practices: Managing Sensitive Data in the Enterprise


While a great deal of attention has been given to protecting companies’ electronic assets from outside threats, organizations must now turn their attention to an equally dangerous situation: data loss from the inside. Given today’s strict regulatory standards, data loss prevention (DLP) has become one of the most critical issues facing executives. Fortunately, effective technical solutions are now available that can help.

difference between data warehouse   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.

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Data Storage in the Cloud-Can you Afford Not To?


Storing data in the cloud using Riverbed Technology’s Whitewater cloud storage gateway overcomes a serious challenge for IT departments: how to manage the vast, and ever-growing, amount of data that must be protected. This paper makes the business case for cloud storage, outlining where capital and operational costs can be eliminated or avoided by using the cloud for backup and archive storage.

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