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Field Service Management (FSM)
Field service management (FSM) software is a set of functionalities for organizations or departments within organizations that have as main focus the intallation, maintanance, reparing, and meter r...
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Documents related to » data mart ilm


Buyer''s Guide to Enterprise Storage Resources
Organizations of all sizes face similar challenges when managing storage@not enough capacity or protection. Help has arrived with Internet small computer system

data mart ilm  the EqualLogic array for data mart and reporting applications. Realizing that simple management and scalability could change his entire operational infrastructure, Monroe decided to virtualize as many servers as possible using VMware and EqualLogic, ultimately consolidating 25 standalone servers for applications ranging from pre-production testing, e-mail and corporate accounting onto 5 servers running VMware. Says Monroe, We would never have done that without the EqualLogic SAN '' that''s what really Read More...
Data Quality Strategy: A Step-by-Step Approach
To realize the benefits of their investments in enterprise computing systems, organizations must have a detailed understanding of the quality of their data—how

data mart ilm  what goes into a data quality strategy? This paper from Business Objects, an SAP company, explores the strategy in the context of data quality. Read More...
Achieving a Successful Data Migration
The data migration phase can consume up to 40 percent of the budget for an application implementation or upgrade. Without separate metrics for migration, data

data mart ilm  a Successful Data Migration Achieving a Successful Data Migration If you receive errors when attempting to view this white paper, please install the latest version of Adobe Reader. Informatica''s data migration solution decreases the risk and minimizes the errors inherent in data migration projects. At the same time, our solution reduces the costs of data migration projects by automating processes, improving business-IT collaboration, and incorporating proven best practices. Source : Read More...
Types of Prefabricated Modular Data Centers
Data center systems or subsystems that are pre-assembled in a factory are often described with terms like prefabricated, containerized, modular, skid-based, pod

data mart ilm  of Prefabricated Modular Data Centers Data center systems or subsystems that are pre-assembled in a factory are often described with terms like prefabricated, containerized, modular, skid-based, pod-based, mobile, portable, self-contained, all-in-one, and more. There are, however, important distinctions between the various types of factory-built building blocks on the market. This paper proposes standard terminology for categorizing the types of prefabricated modular data centers, defines and Read More...
Addressing the Complexities of Remote Data Protection
As companies expand operations into new markets, the percentage of total corporate data in remote offices is increasing. Remote offices have unique backup and

data mart ilm  the Complexities of Remote Data Protection Because data protection is a concern for organizations of all sizes, IBM offers remote data protection for the enterprise, as well. This high performance and easy-to-use service delivers consistent and cost-effective data protection without increased network investment. Source: IBM Resources Related to Addressing the Complexities of Remote Data Protection : Continuous Data Protection (CDP) (Wikipedia) Addressing the Complexities of Remote Data Protection 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

data mart ilm  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. Read More...
Unified Data Management: A Collaboration of Data Disciplines and Business Strategies
In most organizations today, data are managed in isolated silos by independent teams using various data management tools for data quality, integration

data mart ilm  Data Management: A Collaboration of Data Disciplines and Business Strategies In most organizations today, data are managed in isolated silos by independent teams using various data management tools for data quality, integration, governance, and so on. In response to this situation, some organizations are adopting unified data management (UDM), a practice that holistically coordinates teams and integrates tools. This report can help your organization plan and execute effective UDM efforts. Read More...
Tailoring SAP Data Management for Companies of All Sizes
The need for accurate data management such as upload or download of data between a company’s data sources and SAP systems is more critical than ever. Users are

data mart ilm  SAP Data Management for Companies of All Sizes The need for accurate data management such as upload or download of data between a company’s data sources and SAP systems is more critical than ever. Users are relying on manual operations, which are inherently error-prone, and time- and resource-intensive. Today''s environment requires enterprise-class automation to overcome these challenges of data management. Learn about one solution that can help improve SAP data management. Read More...
MSI Data


data mart ilm  Data 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

data mart ilm  Cleansing Customer and Product Data Developing a Universal Approach to Cleansing Customer and Product Data If you receive errors when attempting to view this white paper, please install the latest version of Adobe Reader. Founded in 1972, SAP has a rich history of innovation and growth as a true industry leader. SAP currently has sales and development locations in more than 50 countries worldwide and is listed on several exchanges, including the Frankfurt Stock Exchange and NYSE under the symbol SAP. Read More...
Data Integration: Creating a Trustworthy Data Foundation for Business Intelligence
Organizations combine their historical data with current data from operational systems to satisfy business intelligence analysis and government reporting

data mart ilm  Integration: Creating a Trustworthy Data Foundation for Business Intelligence Organizations combine their historical data with current data from operational systems to satisfy business intelligence analysis and government reporting requirements. This paper discusses the importance of data integration and helps you identify key challenges of integrating data. It also provides an overview of data warehousing and its variations, as well as summarizes the benefits and approaches to integrating data. 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

data mart ilm  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...
Microsoft Goes Their Own Way with Data Warehousing Alliance 2000
Microsoft Corp. (Nasdaq: MSFT) today announced that 47 applications and tools from 39 vendors throughout the industry have qualified for Microsoft« Data

data mart ilm  Their Own Way with Data Warehousing Alliance 2000 Event Summary REDMOND, Wash., Nov. 30 /PRNewswire/ -- Microsoft Corp. (Nasdaq: MSFT) today announced that 47 applications and tools from 39 top vendors throughout the industry have qualified for Microsoft Data Warehousing Alliance 2000. Alliance members and partners are committed to delivering tools and applications based on the Microsoft Data Warehousing Framework 2000, an open architecture for building business intelligence and analytical applications Read More...
Oracle Database 11g for Data Warehousing and Business Intelligence
Oracle Database 11g is a database platform for data warehousing and business intelligence (BI) that includes integrated analytics, and embedded integration and

data mart ilm  Database 11g for Data Warehousing and Business Intelligence Oracle Database 11g is a database platform for data warehousing and business intelligence (BI) that includes integrated analytics, and embedded integration and data-quality. Get an overview of Oracle Database 11g’s capabilities for data warehousing, and learn how Oracle-based BI and data warehouse systems can integrate information, perform fast queries, scale to very large data volumes, and analyze any data. Read More...
Data Management and Analysis
From a business perspective, the role of data management and analysis is crucial. It is not only a resource for gathering new stores of static information; it

data mart ilm  perspective, the role of data management and analysis is crucial. It is not only a resource for gathering new stores of static information; it is also a resource for acquiring knowledge and supporting the decisions companies need to make in all aspects of economic ventures, including mergers and acquisitions (M&As). For organizational growth, all requirements and opportunities must be accurately communicated throughout the value chain. All users—from end users to data professionals—must have the most Read More...

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