Posts

Use Join to Integrate Data in Any Format


Join is a powerful SQL operation implemented across most database types and familiar to database users. Join is typically used to select and combine information from multiple database tables.

Altova MapForce includes a join component for data mapping that works like a SQL join for database tables and extends data integration functionality by empowering users to join data trees of any data format. Anyone familiar with join operations for database tables will find the MapForce join component especially intuitive. A join operation in MapForce can even combine two different data formats and produce output in a new format altogether.

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A Typical MapForce Server Use Case


Envision a manufacturing company that controls costs by exploiting a just-in-time assembly process with a very low supply of parts inventory on hand. New customer orders are logged in a sales database and at the end of every day the components needed to assemble that day’s sales are tabulated.

The IT department runs a SQL query to identify the required parts and transforms the list into a purchase order in JSON format to be transmitted to the supply chain.

Sound familiar? Our recent blog series on JSON tools and JSON data mapping were based on this real-life scenario. In this post we describe a MapForce Server use case that automates the repetitive task of generating each day’s purchase order.

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MapForce Offers Dynamic Access to Node Names


There are situations, especially when encountering loosely structured data, where you may want to map and transform structural components of a data stream along with content. MapForce 2017 includes a new feature to dynamically access node names of XML elements, attributes, or text file columns such as the contents of CSV files, to target components.

Dynamic access to node names allows creation on the fly of target elements and attributes whose names do not need to be known beforehand or specifically identified in the data mapping. This feature lets you create much more generic, flexible, and reusable mappings that require less manual intervention if data models evolve.

News about Dynamic Access to Node Names in MapForce 2017

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Five Not-to-Miss Features in Altova’s Latest Product Release


I’m excited to reveal some details of today’s Release 2 of Altova MissionKit 2016 desktop developer tools and software products!

v2016r2 introduces over 20 new features and updates to the Altova product line – but that’s a lot to cover in one blog post. Let’s take a look at the top five that are sure to blow your socks off.

New in Altova products

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Applying Data Mapping Patterns


Altova MapForce includes powerful mapping components that correspond to design patterns for data transformation requirements. Analyzing a data mapping challenge up front and following a few straightforward guidelines can uncover data mapping patterns that help simplify creation of the mapping design and lead to an optimal solution. The MapForce Examples project provides sample mapping files and data sets that illustrate many common data mapping patterns. Reviewing these examples and executing them with the MapForce Built-in Execution Engine is another good way to help select the best pattern for your own project.

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Interactive Debugger for Data Integration Projects


MapForce 2016 introduces a revolutionary data mapping debugger that lets developers working on data integration projects examine data mapping output step by step to diagnose and perfect projects of any complexity. The MapForce data mapping debugger gives users deep insight into the exact inner workings of data integration and ETL projects in a way that was never before possible.

The debugger works with all MapForce data mappings for any combination of XML, XBRL, JSON, databases, flat files, EDI, Excel, or Web services data, including chained mappings, mappings with multiple input or output components, and mappings that include user-defined functions.

Data Mapping Debugger

The MapForce data mapping debugger supports breakpoints and conditional breakpoints, and includes multiple manual stepping options to manually debug a data mapping or continue execution after a breakpoint is reached, allowing users to see as much detail as they need.
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Data Mapping Files with XML Mixed Content


As more specialized data is adapted for delivery on demand to mobile devices with smaller screens, documents with complex structures can be a challenge. Fortunately, MapForce, Altova’s graphical data mapping, conversion, and integration tool, has special features to accelerate data integration projects of all sizes.

For example, richly-formatted documents may include XML mixed content, a complex datatype that permits an XML element to contain text, attributes, and other child elements. Common instances of XML mixed content include blocks of text with tags for bold or italic fonts, or tags that select terms for indexing or other special treatment. Documents with XML mixed content can be difficult to include in a data integration project, since they appear to be free-form and unpredictable, with child elements that occur in any order or even multiple times within the parent.

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