AI-based Database Image Classification with Altova MapForce


One of the most common examples of AI in our everyday lives is facial recognition. Facial recognition is the process of identifying or verifying a person’s identity based on their face. Facial recognition is used in many applications, such as unlocking our phones with FaceID, tagging our friends on social media platforms like Facebook, and checking in at airports or hotels with biometric scanners. Facial recognition can make our lives more convenient and secure, but it can also raise some privacy and ethical concerns. For instance, how can we ensure that our facial data is not misused or stolen by hackers or malicious actors? How can we prevent facial recognition from being used for surveillance or discrimination? How can we ensure that facial recognition is accurate and fair, and does not have any biases or errors?

The paragraph above was generated by ChatGPT in response to my request to describe the benefits and risks of artificial intelligence and include a real-life example. It’s interesting that ChatGPT chose FaceID as the example, since FaceID is simply one variation of image analysis and AI-powered image classification offers potential to automate many real-world tasks.

One common use-case is a product catalog, wherein a company manages product information provided by many different manufacturers. A product loaded into that database may have a name that does not necessarily include a precise description of the item. For instance, wellington is a boot, fedora is a hat, a mongoose is a bicycle, and a yellow watermelon shiny needlefish is a fishing lure. We can make use of AI-powered image classification using the Microsoft Azure Cognitive Services Computer Vision API to address this problem. The Computer Vision Service takes the image data or URL as its input and returns information about the content. One service generates image classification tags based on a training set of recognizable objects, living beings, scenery, and actions that the Azure AI has been trained on. These tags allow us to categorize products in the database accordingly and may even correspond to search terms a user might provide to find products in the catalog.

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How to Create a Chained Data Transformation


Data mapping plays a vital role in modern data-driven organizations, enabling efficient data management and integration. Altova MapForce is a powerful, graphical data mapping tool that supports endless data transformation scenarios, including one-to-one, one-to-many, many-to-one, and chained data conversion.

While there are applications for each of these approaches, chained data mapping is especially helpful for complex data processing tasks where multiple stages of data manipulation are required. Here’s a look at the benefits of a chained data conversion approach – and a video of how MapForce makes the process easy and straightforward.

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How to Convert Data in MapForce [Video]


Altova MapForce offers a powerful, yet easy-to-use, approach to converting and transforming data. Whether you need to write XML to a database, convert JSON to EDI, or map Excel to multiple different data formats, MapForce has you covered.

From simple one-to-one conversions to complex ETL scenarios, the MapForce approach is to represent data structures as graphical components. To associate fields, drag and drop connecting lines. A comprehensive library of data filters and functions is available for transforming data before writing it to the target.

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We have recently revamped our series of Introduction to MapForce videos. Each short how-to gives a demo of a common MapForce scenario.  

Start at the beginning to learn how MapForce works:

And follow along to learn:

You can follow along with the examples in these how-to videos by downloading a free, 30-day trial of MapForce. Check back for new MapForce videos, which are added often.

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Validating and Debugging Data Transformations


Software developers and other data professionals often need to transform data from one format to another. These transformations can be simple one-to-one conversions or may require more complex manipulation. For instance, relationships must be generated when importing flat CSV files into a database, or source data may need to be split for the target, as in full name vs. first, middle, last, and optional suffix. Validating data transformation is critical to prevent data loss or corruption.

In an earlier post on Web service data integration, we combined a string value for GMT time with a numeric offset in seconds to generate the local time for weather forecasts. We created a user function that performed all the steps required to complete this operation. MapForce includes a powerful interactive data mapping debugger that can easily trace and validate this transformation. Let’s take a look at how it works.

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Benefits of an XML Schema Manager


Developers working with XML often need to deal with multiple DTDs and XSDs that define industry-standard vocabularies. Whether it’s DITA for technical writing, HL7 for healthcare data, CbCR for financial reporting or any number of examples, it becomes a challenge to manage the various schemas—and numerous versions thereof—on a day-to-day basis.

Altova recently introduced a new XML Schema Manager integrated in its XML-enabled products. This provides a centralized utility that makes it easy to download and manage industry schemas for use across the product line. Let’s see how it works.

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ESEF Tools


The ESEF acronym has been top of mind for finance professionals across the EU and UK since mid 2019, when an upcoming reporting mandate from the European Securities and Markets Authority (ESMA) was announced.  

ESEF, which stands for European Single Electronic Format, is a digital financial reporting standard based on XBRL. As of early 2020, companies on EU regulated markets are mandated to prepare their annual reports in accordance with ESEF rules.

What exactly is ESEF compliance, and what does it take to meet reporting requirements? Let’s take a look at the basics and some tools that make it easy.

Finance pros
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Certified Tools for xBRL-JSON & xBRL-CSV


XBRL International has finalized the sunrise period for its important new OIM (Object Information Model), which includes the xBRL-JSON and xBRL-CSV standards. In turn, it has completed the software certification process. Any product awarded the XBRL Certified Software designation has been thoroughly tested by XBRL International for conformance with the current XBRL specifications.

OIM represents a years-long effort of the XBRL community to modernize the financial reporting standard, providing a model for easily transforming XBRL data between XML and other popular formats like CSV and JSON. This way, organizations can take advantage of the functionality of XBRL and at the same time have XBRL documents written in the format(s) most convenient for them.

Altova XMLSpy and RaptorXML Server were some of the very first tools on the market to support xBRL-JSON and xBRL-CSV and are now officially named XBRL Certified Software for the OIM standards (in addition to being certified for a variety of other core XBRL technologies).

Learn more:

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Working with Avro Big Data in Your Favorite XML Editor


Big Data trends have developers working with XML alongside other data protocols such as JSON and Apache Avro, and XMLSpy supports both of these with dedicated editing views and functionality.

Let’s see how specialized Avro support in XMLSpy makes visualizing and searching Avro files, as well as editing Avro schemas, uniquely easy. We’ll also look at some of the advantages of utilizing RaptorXML Server for high-performance Avro processing.

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Automatically Convert EDI to XML


Electronic Data Interchange (EDI) has proven to be a durable business-to-business communication technology in use today with history dating to the 1960s and even earlier. Efficient EDI data encoding reduced transaction payload size and improved data transfer speeds at a time when messages were sent over teletype at speeds equivalent to a 300 baud modem. EDI standards bodies promote wide acceptance among enterprises, and systematic evolution of new EDI formats extends support across industries. EDI improves profitability and is a dominant format for e-commerce data exchange.

Despite the advantages, EDI files are barely human readable and need to be translated and mapped for compatibility with other business technologies. Altova MapForce is a graphical EDI mapping tool with native support for all major business data formats in use today, including XML, JSON, databases, flat files, Excel, and Web services, as well as the EDIFACT, X12, HL7, NCPDP SCRIPT, IDoc, PADIS, and SWIFT EDI transaction sets. MapForce can even automatically convert EDI to XML without the need to specify a target XML Schema or perform any manual mapping.

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How to Compare CSV Files or Compare a CSV File to a Database Table


CSV files are a quick and convenient way to record structured data in a generic format. Because CSV files are so easy to create, multiple similar versions of very large CSV files can quickly proliferate. Often it becomes necessary to compare CSV files to find the desired version. In an ETL scenario, a data analyst may want to compare a CSV file to a database table for validation or to update data.

DiffDog, the unique XML-aware diff / merge tool from Altova, supports CSV as a native file format for comparison and can compare and selectively merge data CSV to CSV, or between a CSV file and database table. Let’s look at an example.

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Analyze JSON Data with Filters, Formulas, and Charts


Software developers and other data professionals often need to examine new data instances before designing processes for efficient production. As JSON becomes a more popular format for data exchange, the tradeoff for smaller data payloads can be loss of clarity of the underlying data structure.

XMLSpy has supported viewing, modeling, and editing JSON files since 2010 and includes rich tools to analyze JSON data, including applying filters, formulas, and charts.

Let’s take a look.

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Excel Data Mapping to Update Existing Documents


Excel began life as a simple spreadsheet tool. Over time, support for rich text styling options, built-in charts, and copy and paste formatting features has led many enterprises to create reports in Excel documents. This can cause difficulty when data changes and existing documents need to be manually updated for distribution to a wide audience in the familiar report style.

Altova MapForce, the award-winning, graphical data mapping tool for any-to-any conversion and integration, supports Excel data mapping to convert data to existing Excel documents while preserving styles and formulas in the original.

This feature lets you write directly to nicely formatted Excel files to update data at runtime: any designated worksheets, rows, and cells from the specified file will be replaced with data from the mapping and all formatting in the existing file will be preserved as-is. To protect functionality in the existing spreadsheet, cells with formulas are not overwritten.

Let’s look at an example of how to map Excel data.

Financial pros using XBRL
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How to Compare XML and Other Files


The ability to diff and merge files is a necessity for every developer. This can be especially troublesome when trying to compare differences between files containing structured data, such as XML.

The video tutorial below provides an explanation on how to compare XML files – and more – using both XMLSpy and DiffDog. These powerful utilities perform diff and merge operations in an XML-aware manner, which reduces the number of false positives seen when comparing files.

Compare XML files with XMLSpy

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Maintaining Low Code Apps


Low code software tools can speed mobile application development by freeing developers from routine coding tasks and encouraging focus on high level app requirements. However, some developers, project managers, and even entire enterprises remain wary of low code tools. These stakeholders are afraid testing and maintaining low-code apps will be more difficult and costly over time.

But not all low code or RMAD (Rapid Mobile App Development) tools are alike. A low code tool that is simply a user interface to a code generator and builds apps from a set of templates could be attractive to an inexperienced developer. When an issue arises, a highly skilled programmer might need to diagnose and modify the generated code for each mobile OS to create a solution.

MobileTogether is a cross-platform RMAD tool that works differently. MobileTogether uses a combination of drag-and-drop UI design, a powerful Action Tree visual language for event handling, and standardized functional programming for data selection and processing. MobileTogether includes a built-in Simulator window to instantly execute the app to test logic, view the UI as it will appear on a variety of iOS, Android, Windows, and other devices, and examine changes in workflow data during execution. MobileTogether also includes sophisticated automated testing features and a built-in debugger to test and debug apps with precision and examine app behavior directly in the design environment.

Let’s look at how some real-world app maintenance requirements are simplified in MobileTogether.

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Tools for JSON Comments and JSON Lines


Altova XMLSpy and MapForce JSON tools have long supported JSON and JSON5 for editing as well as data mapping and conversion. As new JSON formats arise in response to real-world usage, the support in these tools is expanding.

This article will help explain the advantages of two newer formats –  JSON Comments and JSON Lines – and show how to use them in XMLSpy and MapForce.

Tools for JSON Comments and JSON Lines
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Generating a Schema from Multiple XML Instances


I was recently talking with one of our Support Engineers about common questions he receives from customers. One that comes up a lot is schema generation, specifically, “How can I generate an XSD from XML?” The answer, of course, is to use your favorite XML editor. XMLSpy will generate a valid XSD from a DTD, a relational database structure, a JSON Schema, and of course, an XML instance.

But what many customers are surprised to learn is that the XML editor will also create an XML Schema based on a group of related XML files – and this is a common requirement. Let’s take a look at how it works.

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API Data Mapping


Web service data integration with MapForce is a popular and proven strategy to capture timely information for analysis or generation of user-friendly reports. In an earlier post we demonstrated API data mapping in 5-day weather forecasts for busy cargo shipping ports by reading Web service data in JSON format and mapping to richly formatted Excel spreadsheets. The weather API we used  is hosted by OpenWeather, a provider of historical, current, and weather forecast data.

But integrating data from any API is not a set-it-and-forget-it task. When you build a solution based on external data, you have to react quickly when the data structure changes. Since our original integration project OpenWeather revised the data delivered by their API. The API now includes wind gust predictions in a JSON property separate from wind speed. Since wind gusts are suspected as a cause of the recent Suez Canal blockage the new data is very relevant to our application! Fortunately, both the MapForce data mapping and the Excel spreadsheet are easily revised to add new data.

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Developing and Debugging User Functions in Mobile Apps


Recently I came across this note in a senior developer’s code review of a colleague’s work: “Slightly revised the user function to work correctly when languages other than English are used.” This was a surprising comment–the code is the code and it shouldn’t make a difference what language the developer or the end user speaks! A user function is simply an expression that may accept input parameters and returns a result.

Altova MobileTogether supports user functions in a cross-platform mobile development framework that combines drag-and-drop UI design and standardized functional programming for data selection and processing. Several MobileTogether demo applications are highly dependent on user functions and the MobileTogether Designer includes features that greatly assist creating and validating user functions.

Let’s take a look at user functions in mobile apps by examining one of these demo apps.

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New XML Grid and More in v2021r2


In the latest release of Altova desktop developer tools and server software products, we’re introducing a completely rebuilt XML Grid View, support for XSLT3 for XML data mapping, statistics and charts for monitoring FlowForce Server, and much more. Let’s take a look at the highlights of Altova Software Version 2021 Release 2. 

New features in Altova v2021r2
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New JSON Editing Features


In Version 2020, Altova introduced an entirely new approach to JSON editing in XMLSpy called JSON Grid View. This visual JSON editor offers a graphical representation of the JSON document structure that is immediately easier to understand and work with than the corresponding JSON code in a text editor, especially for long, complex documents with multiple nested levels of arrays and objects.

With each release we improve upon the list of unique editing tools in JSON Grid. Let’s take a look at  some important updates announced in Version 2021, which was released in October of 2020.

New JSON editing tools
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Data Mapping Binary Objects – Part 2


Binary objects – BLOBs — can be cumbersome to manage in databases. In an earlier post we described a MapForce data mapping to insert binary objects into a database with generated metadata to identify the BLOBs later. The companion challenge in data mapping binary objects is to extract binary data and save it in a comprehensible form faithful to the original.

Let’s look at how that’s done.

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Data Mapping Binary Objects


Binary objects are difficult to manage in databases. They are large, their content is not human readable, and they can contain bytes of data easily misinterpreted as control characters. Even the data type name for binary large objects – BLOB – reflects most database managers’ dislike of them. Before relational databases, the definition of a blob was “something undefined or amorphous.”

Altova MapForce, the award-winning, graphical data mapping tool for any-to-any conversion and integration, includes features for effortlessly data mapping binary objects to or from all popular relational databases. Data such as images, PDF files, video files, or any other binary data can be mapped. Let’s look at an example.

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Mobile App Debugging


MobileTogether is a tool for building highly complex, elegant, cross-platform solutions. Developers need mobile app debugging tools to troubleshoot during development and understand app behavior. The MobileTogether Designer offers full-featured debugging of app execution flow inside action trees and debugging of XPath/XQuery functions. These features are provided in two mobile app debugging views integrated into a single tool.

The Actions Debugger view allows developers to debug the Actions of a Control event or a Page event. This view is available when an Action that has been selected for debugging is encountered during processing. The XPath Debugger view opens the XPath/XQuery evaluator window for in-depth tracing and debugging of expressions.

Developers can set breakpoints at various locations and the app, then execute one step at a time, pausing in either view to allow examination of the complete execution environment.

Let’s see mobile app debugging in action:

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Design Templates for Mobile Apps


In an earlier post we wrote about using software design templates for mobile apps to facilitate design reuse and make it easy to build efficient, flexible options for various app requirements. We described an example of a Control Template designed to present multiple levels of hierarchical data based on user selection at runtime.

Our example was built using MobileTogether, Altova’s RMAD (Rapid Mobile App Development) tool to help developers build cross-platform apps that deliver dynamic, sophisticated app performance that delights end users.

You can also build Control Templates for cross-platform mobile apps by combining multiple controls into a larger unit, like a complex sub-assembly built from individual parts. This creates design templates for mobile apps that can easily be dropped in anywhere, speeding development and ensuring consistency.

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Programming Techniques for Mobile Development


MobileTogether is an easy to use, low-code app development framework that lets you create sophisticated apps for all platforms from a single design.

Low-code doesn’t mean no code. A database specialist might start with a few SQL queries and use the MobileTogether drag and drop interface to create an app with elegant tables and graphs to report up-to-the-minute enterprise data, while experienced developers often use familiar programming techniques in mobile development to build highly complex, elegant MobileTogether solutions.

Developers define user functions, parameters, variables, loops, or a complex data structure when that’s the right tool for the job. MobileTogether makes it fast and easy to control all the features in the device – camera, microphone, GPS, SMS, handwriting capture, and more. MobileTogether helps you achieve your vision fast and build really cool mobile apps with charisma enough to go viral.

MobileTogether is about getting the work done efficiently, not limiting how you do it. Let’s check out a couple examples of programming techniques in MobileTogether apps.

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Web Service Data Integration


In a previous post we wrote that every data integration and reporting task needs to start with a clear understanding of the source data. Using grid view in XMLSpy, the industry-leading XML and JSON editor, we analyzed JSON data for 5-day weather forecasts retrieved from a Web service.

Continuing with our earlier scenario, we’ll use MapForce, the award-winning, graphical data mapping tool for any-to-any conversion and integration, to map the forecasts for a series of major cargo shipping ports into nicely formatted Excel documents. We’ll want to highlight any predicted high winds or heavy rainfall that could cause delays by interfering with cranes loading and unloading containers, or slowing ships entering and exiting the harbors.

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New Tools to Work with XBRL in Excel


With the importance of accurate, standardized financial reporting enforced through XBRL filing mandates, having XBRL tools you can rely on is a must. What’s more, financial professionals need to be able to generate XBRL reports easily without getting bogged down by the complexities of XBRL syntax.

Altova offers several add-ins for Excel that make it easy for organizations to comply with regulations from the EBA, EIOPA, and other regulatory bodies that mandate reporting in XBRL. These easy-to-use software products integrate directly into Excel so that users can create valid XBRL reports in an environment where they’re already comfortable working. And, the add-ins support importing existing XBRL reports to Excel for easy readability and analysis.

The latest release of the Altova XBRL Add-ins for Excel provides some important new features – let’s take a look.

New tools to work with XBRL data in Excel
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How to Convert Legacy Text Files [Video]


It’s a common requirement to convert non-standard or legacy text files to or from structured data formats like XML, JSON, and relational databases. However, many times legacy text files are not in a format that can be readily processed by data mapping tools, especially when they have a complex and unique structure that does not consistently fit into CSV or fixed-length field patterns. Moreover, sometimes you need to extract only portions of useful data from a legacy text file.

MapForce, Altova’s any-to-any data conversion tool, includes a unique utility called FlexText that makes it easy to visually define templates for parsing text files and making them accessible to the data mapping tool.

See how FlexText works in our video tutorial.

The example files referenced in the video are available here and you can try FlexText with a free, 30-day trial of MapForce.

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Software Design Templates in Mobile Development Projects


Software design templates streamline mobile app development by eliminating implementation of repetitive components. Creating a design template also simplifies revisions and upgrades when a change to the template can roll through an entire project.

MobileTogether supports software design templates for user controls in cross-platform mobile apps to facilitate design reuse and make it easy to build efficient, flexible options for various app requirements.

A Control Template in MobileTogether is a design component that allows developers to specify and group user controls in a way that makes them easily reusable. Control Templates support parameters, and each template can be customized based on parameter values at runtime.

Let’s look at an example.

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UML Modeling for C++ with UModel


C++ is one of the most powerful and efficient programming languages available, the de facto choice for high-performance computing, server applications, and complex architectures that demand the most powerful language constructs. The Unified Modeling Language™ (UML®) is the standard to design, visualize, and document models of software systems implemented in C++ and other source code languages.

Altova UModel competes with even the most advanced UML modeling tools with complete code engineering support in UML modeling for C++. UModel includes: C++ code generation from UML diagrams, reverse engineering C++ code to generate UML models, and round-trip engineering to update revisions to either C++ code and UML models.

Model transformation even lets developers convert an existing UML model designed for Java, C#, or Visual Basic to support C++.

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Handle HTTP Errors During Automated Data Integration


Data analysts and other professionals often need to generate real-time data through automated execution of data mappings that request Web services and save the results. During automated execution it’s important to gracefully handle any unexpected HTTP error rather than terminate the integration task.

In an earlier post we discussed conditional processing of a REST Web service response to handle HTTP errors, where separate output files were generated for a normal response and an error. Now let’s look at a revised mapping solution for the airport status example to generate a single mapping result file that contains either the requested airport status or a description of the error.

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How to Manage GDPR Compliance [Video]


The General Data Protection Regulation, better known as the GDPR, is a set of privacy and data protection rules applying to organizations that process personal data of people residing in either the European Union or European Economic Area. It was built to comply with legislation that went into effect on May 25, 2018 and provides individuals more control of their personal data. The GDPR simplifies the regulatory environment for international business by providing a common set of standards for all businesses working in the EU.

The GDPR requires that data production measures be built into the design of business processes that collect personal data. If a breach occurs, information about this breach must be reported to the supervisory authority. Altova has created the GDPR Compliance Database, a tool that simplifies the storage and access of metadata related to company processes that touch personal data.

The Altova GDPR Compliance Database is a long-term solution for companies looking for a permanent solution to GDPR compliance. It enables companies to respond quickly to any incidents and contains built in mechanisms for change tracking, ensuring compliance measures are well documented.

The video above provides a high-level overview of all the features contained in the Altova GDPR Database.

Learn more about the Altova GDPR Compliance Database and try it free for 30 days.

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Handling HTTP Errors in Web Service Data Mappings


Data integration projects that include information from external Web services may be vulnerable to HTTP errors when retrieving remote data. When data mappings run under automated control it’s especially important to detect and report errors even if errors only occur very rarely.

A MapForce data mapping can include Web service calls and output the result directly to a file or database, or combine it with other inputs for further processing. Regardless of the final output, an HTTP Web service error encountered in a REST Web service request puts the mapping at risk.

MapForce includes features for handling HTTP errors instead of simply aborting execution of a mapping. Developers can configure the body of a REST Web service call to handle and report exceptions based on the HTTP status code returned.

Let’s look at an example.

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How to Generate CbC Correction Reports


Altova’s Country by Country (CbC) Reporting Solution makes it easy for multi-national companies to generate valid XML reports to meet the filing requirements mandated by the OECD. Now, in Version 2.0, the CbC Reporting Solution includes new functionality for generating correction reports, as well as the ability to import existing reports for easy analysis.

Let’s take a look at how these new tools make it even easier for customers to meet filing requirements without having to deal with the underlying CbCR XML syntax.

Country by Country Reporting Solution for XML
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Automatic Link Detection for Mobile Apps


Integration between a mobile app and the vast information resources of world wide web makes the user experience more convenient and responsive, especially when targeted web content may be frequently updated.

The latest release of MobileTogether, Altova’s low-code, cross-platform mobile development framework, includes support for automatic link detection of URLs and email addresses in labels. Clicking or tapping the link opens the targeted website page in a browser window or as a new draft message in the device’s email app in a new window without quitting the mobile app. No further special coding required by the developer.

User interacting with app

Let’s see how it works.

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Automate Word Document Comparison in Busy Enterprises


Many enterprises and business situations leverage Microsoft Word documents in standardized formats, with variations in content in subsequent versions. Think of contracts or other legal documents, status reports, test results, lists of rules, and many others. These documents may even be generated through automated processes. Manually identifying and reporting changes between versions would be a cumbersome process. Altova DiffDog Server provides an efficient, automated solution.

DiffDog Server brings the file and directory comparison power of Altova DiffDog to high-performance servers, making it easy to automate Word document comparison and generate diff reports comparing files, directories, or URLs, and even Word documents (.docx) saved in MS Office versions 2007 or later.

Let’s look at a Word document comparison.

Automate Word document comparison with DiffDog Server
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Mapping Structured Data with Enhanced Node Functions


We’ve reported previously on support for node functions that simplify mapping structured data by eliminating need to copy-paste a function multiple times into a mapping. Repeating the same function unnecessarily clutters the mapping layout and makes the data mapping more difficult to understand or revise.

Now in MapForce 2019, additional filters are available for defining node functions. These new parameters allow developers to apply functions and default values to specific nodes based on custom-defined criteria. For example, you can apply a node function based on node metadata such as the node name, node length, precision of the node’s data type, customized node annotations, and more.

Let’s look at a mapping with enhanced node functions.

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Node Functions Simplify Mapping Hierarchical Data Structures


MapForce node functions simplify mapping hierarchical data such as XML nodes or CSV, JSON, EDI, or database fields by permitting users to define a data processing function at the node level and apply it recursively to all descendant items.

Similarly, default values can also be assigned to nodes and automatically applied to descendants.

Defaults and node functions are particularly useful when a data mapping and transformation task requires the same processing logic for multiple descendant items in a structure, for example:

  • Replace null values with some other value, recursively for all descendant items
  • Replace a specific value (for example, “N/A”) with some other value recursively for all descendant items
  • Replace all database null values when reading from a database table
  • Trim all trailing spaces for all values from a source database
  • Append a custom prefix or suffix to all values written to a target file or database
  • Formatting of output values
  • And many others

Defaults and node functions simplify mapping hierarchical data by eliminating need to copy-paste the same function multiple times into a mapping. Repeating the same function unnecessarily clutters the mapping layout and makes it more difficult to understand or revise.

Let’s look at an example.

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The Only JSON Dev Tool You’ll Need


While XMLSpy might not be the first tool developers think of when they’ve got a JSON development task, XMLSpy includes comprehensive support for working with JSON, JSON Schema, and related technologies.

Over the past few product releases, we’ve added intelligent functionality for editing and converting JSON and JSON5 data to the product. We’ve completed the circle with one-click conversion between XML Schemas and JSON Schemas, as well as sample instance generation and JSON Schema documentation generation. And, most recently, we’ve added support for processing JSON with XSLT,  XPath, and XQuery.

Let’s walk through some common examples demonstrating this functionality – and see how these time-saving tools make XMLSpy the only JSON development tool you’ll need.

Developer using JSON tool

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Automate Diff Report Generation


DiffDog Server makes it easy to automate high-volume comparisons and generate diff reports comparing files, directories, and URLs. This high-performance server software is available for Windows, Linux, and MacOS X machines.

Developers have long relied on DiffDog for comparing XML, text, and binary files, as well as directories and URLs. Now, the power of DiffDog is available in lightning-fast server software for easily automating large comparison tasks.

For instance, DiffDog Server is perfect to automate diff report generation for critical files and directories at a given time – every day, once a week, etc.

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The Importance of Choosing Certified XBRL Tools 


Aside from complying with filing regulations, there are numerous benefits associated with adoption of the eXtensible Business Reporting Language. Standardizing information allows data validation as well as simplified comparison of reported data within an organization – from quarter to quarter or year to year, for instance – as well as comparing performance among multiple companies.

Of course, the benefits promised by XBRL  can only be realized through strict standards conformance in the tools organizations use for validating, reporting, and analyzing their XBRL data. Problems have arisen due to lack of consistent interoperability between software tools as well as less stringent validation checks that result in filing errors and diminished data quality.

Altova has always striven to deliver the closest possible conformance with supported XBRL standards and is honored to have received certification from multiple XBRL standards bodies, ensuring conformance and interoperability. Let’s take a look at the specifics and why this is so important for customers.

Financial pros using XBRL

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Inform Users with Sound Effects in Mobile Apps


Sound effects in mobile apps can reinforce functionality and make an app more fun to use. MobileTogether makes it easy and convenient for mobile developers to add a standard set of sounds to user interface actions across all mobile platforms. For instance, developers might want to add sound effects to signify the success or failure of a file transfer or database transaction. Or simply add a keyclick sound to a button as feedback for a user tap.

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Multi-Language Localization for Mobile Apps


MobileTogether includes support to seamlessly localize mobile apps in multiple languages. This empowers developers to build one version of a mobile app that works across many languages as well as across multiple platforms.

Developers can include translations in a single MobileTogether app design for all text phrases required, and when any end-user runs the app, whether on an Android phone, an iPhone, Windows desktop, or any other supported platform, the language for the app is selected to match the language for the device operating system.

With multi-language localization, even text-to-speech functionality is localized to the user’s native language.

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SQL Queries with Parameters: Support for SQL Templates in DatabaseSpy


SQL queries with parameters, also known as SQL templates, are a flexible and efficient solution for repetitive data reporting requirements, for instance allowing users to easily execute complex join statements with multiple sets of values. DatabaseSpy, the multi-database query, design, and editing tool from Altova, includes robust support for developing, executing, and refining complex SQL queries with parameters, also known as SQL templates.

Prototyping SQL queries with parameters in DatabaseSpy can even accelerate development of queries required in other projects such as database mappings in MapForce or database data sources for MobileTogether cross-platform mobile apps.

Big Data Support

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Three-Way File Comparison and Difference Merging


Manually comparing versions of a long XML Schema or document to find any differences would be a tedious and error-prone task. XMLSpy has long featured file comparison with highlighted differences in side-by-side windows with merging in either direction. And of course, DiffDog is the go-to comparison utility for text, source code, XML, JSON, and Word documents. Now both XMLSpy and DiffDog support three-way file comparison and difference merging.

Three-way file comparison is especially relevant for files managed in any source control system where two users may have started from the same source file and made different edits that need to be reconciled.

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Add to Your Collection of Development Building Blocks


When it comes to developing sophisticated software and data integration applications, the more building blocks a developer has at his or her disposal, the better. With each release of our developer and server software, we aim to provide customers with unique tools that give them the edge to get the job done – faster, and more efficiently.

To that end, Version 2018 delivers a unique HTTP testing window, 3-way file comparison functionality, support for SQL Templates, super-powered new server options, and much more.

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Text-to-Speech for Mobile Apps


Altova MobileTogether supports text-to-speech functionality for cross-platform mobile apps, empowering developers to add speech and build a rich multi-media user experience.

Speech can be fully integrated with text anywhere it appears in an app. For instance, an app like the Parcel Delivery MobileTogether example can be enhanced by speaking the next delivery address aloud – especially if the driver is in traffic! Or, text in message boxes of other information blocks can also be spoken by the mobile device.

We created a simple demo to experiment with the functionality of text-to-speech for mobile apps then added text-to-speech features to the Parcel Delivery app.

Text-to-speech for mobile apps

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Exploring an Unfamiliar Database with DatabaseSpy


Software developers working on a new app, data professionals in a variety of enterprises, and even database administrators often encounter unfamiliar databases and need a database tool to quickly explore tables and relationships.

Altova DatabaseSpy is a unique multi-database query, design, and comparison tool with a graphical database design editor that empowers users exploring an unfamiliar database to quickly visualize tables, relationships, and even datatype definitions that may be unique among database types.

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