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Master Data Management and Accurate Data Matching
Have you ever received a call from your existing long-distance phone company asking you to switch to its service and wondered why they are calling? Chances are

data matching  Data Management and Accurate Data Matching Have you ever received a call from your existing long-distance phone company asking you to switch to its service and wondered why they are calling? Chances are the integrity of its data is so poor that the company has no idea who many of its customers are. The fact is, many businesses suffer from this same problem. The solution: implement a master data management (MDM) system that uses an accurate data matching process. Read More...
Outsourcing, IT Infrastructure
The IT Infrastructure Outsourcing knowledge base focuses on the selection of companies who provide outsource services in the areas of information technology (IT) infrastructure. The typical type...
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Documents related to » data matching


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

data matching  rows, etc. 4. Matching Data matching consolidates data records into identifiable groups and links/merges related records within or across data sets. This process locates matches in any combination of over 35 different components — from common ones like address, city, state, ZIP', name, and phone — to other not-so-common elements like email address, company, gender and social security number. You can select from exact matching, Soundex, or Phonetics matching which recognizes phonemes like ph and Read More...
The Hidden Role of Data Quality in E-Commerce Success
Successful e-commerce relies on intelligible, trustworthy content. To achieve this, companies need a complete solution at their back- and front-ends, so they

data matching  under conditions in which data is inconsistent or missing. An inbound transaction or user search must be joined to an optimal set of matches from thousands, even millions, of choices in the database. Vendor software uses sophisticated database indexing and search optimization strategies to achieve speed and yield. Fuzzy matching and filtering - for measuring and ranking possible matches to get the best one(s) and avoid irrelevant matches. In search engines, this technology returns only the most useful 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

data matching  between two sets of data values. Software that provides fuzzy matching capabilities often has underlying libraries that provide knowledge that cannot be discerned purely from text (or phonetic) similarities. For instance, the knowledge that a developer and programmer must be considered the same job title is required to successfully match job titles that have little or no textual similarity. Most tools also provide the possibility to customize matching rules and create more complex rules tailored to Read More...
A Road Map to Data Migration Success
Many significant business initiatives and large IT projects depend upon a successful data migration. But when migrated data is transformed for new uses, project

data matching  a best of instance. Data quality matching could also be used to eliminate duplicate data within a single source. This logic could be implemented to select a best of record that will later be evaluated by a data expert. The logic and the process to identify the ‘good record' should be part of your mapping specification. Allow time to look at the data. Don't allow your team to fall into the trap of mapping based on column names, copybooks (remember those?), or DDL. For each subject area, you should Read More...
A Definition of Data Warehousing
There is a great deal of confusion over the meaning of data warehousing. Simply defined, a data warehouse is a place for data, whereas data warehousing

data matching  Definition of Data Warehousing Biographical Information Bill Inmon Bill Inmon is universally recognized as the father of the data warehouse. He has over 26 years of database technology management experience and data warehouse design expertise, and has published 36 books and more than 350 articles in major computer journals. His books have been translated into nine languages. He is known globally for his seminars on developing data warehouses and has been a keynote speaker for every major computing Read More...
Appliance Power: Crunching Data Warehousing Workloads Faster and Cheaper than Ever
Appliances are taking up permanent residence in the data warehouse (DW). The reason: they are preconfigured, support quick deployment, and accelerate online

data matching  Power: Crunching Data Warehousing Workloads Faster and Cheaper than Ever Appliances are taking up permanent residence in the data warehouse (DW). The reason: they are preconfigured, support quick deployment, and accelerate online analytical processing (OLAP) queries against large, multidimensional data sets. Discover the core criteria you should use to evaluate DW appliances, including performance, functionality, flexibility, scalability, manageability, integration, and extensibility. 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

data matching  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 Read More...
The Use of Ceiling-Ducted Air Containment in Data Centers
Ducting hot IT-equipment exhaust to a drop ceiling can be an effective air management strategy, improving the reliability and energy efficiency of a data center

data matching  Ceiling-Ducted Air Containment in Data Centers Ducting hot IT-equipment exhaust to a drop ceiling can be an effective air management strategy, improving the reliability and energy efficiency of a data center. Typical approaches include ducting either individual racks or entire hot aisles and may be passive (ducting only) or active (include fans). This paper examines available ducting options and explains how such systems should be deployed and operated. Practical cooling limits are established and Read More...
A Solution to Data Capture and Data Processing Challenges
Organizations are relying more and more on customer information to drive business processes. You probably spend a lot of time trying to make sure you get the

data matching  Solution to Data Capture and Data Processing Challenges Organizations are relying more and more on customer information to drive business processes. You probably spend a lot of time trying to make sure you get the right information to the right people at the right time—but is your data capture process as efficient as it could be? Learn about the issues surrounding data capture and data processing, and about a solution designed to help you address specific processing problems. 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 matching  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...
Deploying High-density Zones in a Low-density Data Center
New power and cooling technology allows for a simple and rapid deployment of self-contained high-density zones within an existing or new low-density data center

data matching  Zones in a Low-density Data Center Deploying High-Density Zones in a Low-Density Data Center If you receive errors when attempting to view this white paper, please install the latest version of Adobe Reader. Together, APC’s global teams work to fulfill their mission of creating delighted customers. To do this, the Company focuses its efforts on four primary application areas: Home/Small Office; Business Networks; Data Centers and Facilities; and Access Provider Networks. Source : APC Resources 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

data matching  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 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 matching  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...

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