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Ardent Software Enters the SAP Data Extraction Market
Ardent Software has announced the addition of SAP extraction and load capabilities to their DataStage product, increasing their strength in the Extract

data extraction  Software Enters the SAP Data Extraction Market Event Summary Ardent Software, Incorporated of Westboro, Massachusetts (NASDAQ: ARDT) has announced support for extraction from SAP R/3 and also loading to SAP BW (Business Information Warehouse) using its DataStage Release 3.6. Ardent is referring to the new feature as the Packaged Application Connection Kit (PACK). With the DataStage Extract PACK for SAP R/3, users will be able to extract data directly from SAP R/3 systems natively and integrate it with 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 extraction


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

data extraction  Data Integration: A Primer Originally published - August 22, 2006 Introduction Implementing a customer data management 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. Read More...
About Big Data
There may not be a consensus with respect to just how big

data extraction  and unstructured content. The data extraction process can be especially difficult with large amounts of information. These new tools are changing the traditional BI data cycle. Data can be collected from its sources and analyzed in a matter of seconds, giving reliable results in a fraction of the time required by a traditional BI deployment, thus reducing data latency and speeding up the decision-making process. Some of the advantages of deploying a big data solution include: reducing the decision-making 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 extraction  Cost Data Migration | Data Storage | Extraction and Loading | Programmatic Data Migration | Storage Migration | Database Migration | Application Migration | Standard ETL Technologies | Migration Procedure | Read More...
Collecting Meaningful Data from the Web: Once an Impossibility, Now a Reality
The traditional way of extracting data from disparate data sources has been transformed by the emergence of new tools and applications, as well as the

data extraction  systems, other types of data extraction have become necessary. Organizations now require alternative ways to collect information coming from vast amounts of external Web pages, for such purposes as monitoring customer sentiment, measuring marketing results, and collecting Web content for research purposes. But for this type of data extraction, companies may not have an API available, either because an API for this does not exist, or because the company simply does not have access to it. Also, some Read More...
Master Data Management: Extracting Value from Your Most Important Intangible Asset
In a 2006 SAP survey, 93 percent of respondents experienced data management issues during their most recent projects. The problem: many organizations believe

data extraction  Data Management: Extracting Value from Your Most Important Intangible Asset Master Data Management: Extracting Value from Your Most Important Intangible Asset 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 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 extraction  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...
Optimizing Gross Margin over Continously Cleansed Data
Imperfect product data can erode your gross margin, frustrate both your customers and your employees, and slow new sales opportunities. The proven safeguards

data extraction  Margin over Continously Cleansed Data Optimizing Gross Margin over Continously Cleansed Data If you receive errors when attempting to view this white paper, please install the latest version of Adobe Reader. Advanced functionality to manage costs, sell prices, promotions, discounts, chargebacks, and other key attributes while optimizing gross profits. Source : epaCUBE Resources Related to Optimizing Gross Margin over Continously Cleansed Data : Data cleansing (Wikipedia) Gross margin (Wikipedia) Read More...
Data Storage in the Cloud--Can You Afford Not To?
In Data Storage in the Cloud Can You Afford Not To?

data extraction  Afford Not To? Spiraling data storage requirements are straining many companies' abilities to keep pace. One obvious solution is storage in the cloud—but concerns regarding security, speed, and accessibility remain. Or do they? In Data Storage in the Cloud—Can You Afford Not To? , you'll discover a cloud storage solution that offers you high-security dual-level encryption (SSLv3 and 256-bit AES) data accessibility from anywhere lower costs due to the economies of scale of cloud storage providers high Read More...
Transactional Data: Driving Real-Time Business
A global survey of IT leaders shows that most organizations find it challenging to convert high volumes of fresh transactional data into knowledge that business

data extraction  volumes of fresh transactional data into knowledge that business users can efficiently access, understand, and act on. SAP and HP are tackling this challenge head-on. Download this article to learn more. Read More...
Data Migration Best Practices
Large-scale data migrations can be challenging, but with the appropriate planning—and through careful execution of that plan—organizations can greatly reduce

data extraction  Migration Best Practices Large-scale data migrations can be challenging, but with the appropriate planning—and through careful execution of that plan—organizations can greatly reduce the risks and costs associated with these projects. This paper offers a handy checklist of issues to consider before, during, and after migration. Read More...
Massive Data Requires Massive Measures
One thing we learned in the data warehouse and data management world is that when it comes to the analysis of big data, there is also a lot of big money

data extraction  Data Requires Massive Measures   From Sun Tzu’s The Art of War : In the operations of war, where there are in the field a thousand swift chariots, as many heavy chariots, and a hundred thousand mail-clad soldiers, with provisions enough to carry them a thousand Li, the expenditure at home and at the front, including entertainment of guests, small items such as glue and paint, and sums spent on chariots and armor, will reach the total of a thousand ounces of silver per day. Such is the cost of 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 extraction  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 extraction  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...
Scalable Data Quality: A Seven-step Plan for Any Size Organization
Every record that fails to meet standards of quality can lead to lost revenue or unnecessary costs. A well-executed data quality initiative isn’t difficult, but

data extraction  Data Quality: A Seven-step Plan for Any Size Organization Melissa Data’s Data Quality Suite operates like a data quality firewall – instantly verifying, cleaning, and standardizing your contact data at point of entry, before it enters your database. Source : Melissa Data Resources Related to Scalable Data Quality: A Seven-step Plan for Any Size Organization : Data quality (Wikipedia) Scalable Data Quality: A Seven-step Plan for Any Size Organization Data Quality is also known as : Customer Read More...

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