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Altova Mapforce

Data Integration

Comelio Altova MapforceThe data integration process can often seem overwhelming, and this is often compounded by the vast number of large-scale, complex, and costly enterprise integration applications available on the market. MapForce seeks to alleviate this burden with powerful data integration capabilities built into a straightforward graphical user interface.

MapForce lets you easily integrate data from multiple files or split data from one file into many. Multiple files can be specified through support for wildcard characters (e.g., ? or *), a database table, auto-number sequences, or other methods. This feature is very useful in a wide variety of data integration scenarios; for example, it may be necessary to integrate data from a file collection or to generate individual XML files for each main table record in a large database. The screenshot below shows an example in which two files from a directory are integrated into a single target file.

XML Mapping

Comelio Altova MapforceAltova MapForce® 2010 provides powerful, visual XML mapping functionality for instantly transforming XML data from one XML format to any another XML format based on XML Schema or namespace aware DTDs, and can even generate an XML mapping component from an XML instance file.

Developing XML Mappings

Comelio Altova MapforceMapForce provides an intuitive graphical interface for defining and executing XML mappings based on XML Schema or DTD content models. To develop an XML mapping, simply load two or more schemas into MapForce and drag connecting lines between the nodes of the source(s) and target(s), as shown below. Mixed content support even enables you to map text data that is interspersed with XML. To make your mapping easier, MapForce automatically connects matching child elements as you create your XML mapping by default (this setting can be changed at any time in the Connection menu).

Advanced Data Processing for XML Mappings

Comelio Altova MapforceXML mapping projects are often not simply one-to-one mappings of a source to a target component with the same structure. Most XML mappings involve the use of data processing functions to manipulate data between the content models. You may need to perform logical comparisons, mathematical computations, or string operations, and/or make other modifications to the data to complete your mapping. Data processing functions appear as boxes between the lines joining the source and target XML mapping components.

Data processing functions enable you perform advanced data transformations on-the-fly for a multitude of real-world transformation requirements. You can, for example, map multiple XML source elements to one target XML element to map European and US addresses to one generic “address” field, or easily convert incongruous date/time formats.

MapForce also supports advanced XML transformations involving multiple input and output schemas, multiple source and/or target files, or advanced multi-pass data transformations (from schema, to schema, to schema, etc.), for which you simply insert additional XML Schemas or DTDs into MapForce and draw additional XML mappings.

Text mapping

Comelio Altova MapforceAltova MapForce® 2010 includes flexible support for integrating flat files with XML, database, EDI, Excel 2007+, and XBRL data and for mapping flat file data to Web services operations.

Developing Flat File Mappings

Comelio Altova MapforceFlat files such as CSV (comma-separated values) and text documents are employed by many different applications and are often used as an exchange format between dissimilar programs. As companies continue to expand and grow through globalization and mergers and acquisitions, the ability to programmatically integrate or convert this semi-structured data into other prevalent formats is a common requirement.

Many organizations continue to utilize legacy software that can no longer be modified, but produces useful output in the form of text files. Integrating these applications into a modern computing environment can be challenging. The structure of flat files and text documents varies from application to application, making processing and integrating this data with other data formats increasingly difficult.

MapForce supports flat files as both the source and target of any mapping. MapForce does not limit you to one-to-one mappings - you can mix multiple sources and multiple targets to map any combination of data formats.

EDI Mapping

Comelio Altova MapforceAltova MapForce® 2010 allows you to map EDI messages to and from XML, databases, flat files, Excel 2007+, and Web services. Full support for the UN/EDIFACT, ANSI X12, Health Level 7 (HL7), and SAP IDoc standards means that you can seamlessly integrate this data with other systems to meet the changing demands of business partners and customers, internal requirements, and global data transmission mandates.

EDI standards have been the dominant format for e-commerce data exchange for decades, and give organizations a fast and accurate method of transmitting transaction data without the need for human interaction. However, as a message transmission paradigm, EDI is source format and system agnostic, and requires translation and purposing for delivery to proprietary systems at its final destination. The reality that EDI precedes such prevalent integrated business technologies as ERP, CRM, many database formats, and many other supply chain enabling technologies, makes data mapping and transformation an important component of any EDI implementation.

XBRL Mapping

Comelio Altova MapforceAltova MapForce® 2010 provides powerful support for producing interactive financial data that complies with the XBRL and XBRL Dimensions specifications as well as the ability to easily aggregate XBRL data for financial analysis.

Extensible Business Reporting Language (XBRL) is an XML-based markup language for electronic transmission of business and financial data. With a brand new mandate from the United States Securities and Exchange Commission (SEC), and official support from European Parliament as well as the governments of Japan and China, XBRL aims to reduce costs through the elimination of time consuming and error-prone human interaction. The introduction of XBRL tags allows computers to process information independently, thus increasing the speed of data integration and exchange, while at the same time virtually eliminating data redundancy and quality issues.

XBRL adoption gives companies the opportunity to introduce new efficiencies into their financial reporting workflow, preventing redundant tasks by automating data extraction and increasing accuracy through the validation of both syntax and semantics.

MapForce supports the use of XBRL taxonomies as the source or target of any mapping, enabling you to graphically transform backend accounting data into a compliant format without any risk to its semantic or structural integrity and/or integrate reporting data for financial analysis. Support for code generation in Java, C#, or C++ means that you can also automate the conversion of financial data based on the graphical mapping design. This makes public financial data submission a repeatable and highly manageable process, allowing you to produce valid XBRL reports as required based on the variable data stored in accounting system fields.