Apps built with MobileTogether include the ability to use SSL encryption between the mobile app and the back-end server, and with it come restrictions on importing and exporting the app in the United States and potentially other countries. If you intend to submit the AppStore App to Apple’s App Store or Microsoft’s App Store (and potentially others), their submission processes will ask whether the app includes encryption. Since all AppStore Apps built with MobileTogether include the ability to use the OS-provided libraries for SSL use in mobile apps and in particular for the encryption of the communication between the mobile app and server using the https protocol, the answer to this question is “YES.” At some point in the process, this answer will then trigger a prompt to upload your Encryption Registration Number (ERN). So how does one obtain an ERN?
To match the speed of business, mobile app development must be simple, fast, and efficient. Your apps must meet user demands on all platforms and mobilize essential processes seamlessly. Sounds easy enough, right? With MobileTogether, it is.
In true version 2.0 fashion, MobileTogether delivers the final piece of the puzzle: you can build your own, custom-branded app to submit to the app stores.
The new AppStore Deployment process is well suited for customer-facing or specially-branded apps. This option adds to existing support for Instant Deployment of enterprise app solutions using the MobileTogether Mobile Apps. With either approach, you’ll still get your app in end users’ hands in record time – much faster than any other approach.
In a previous blog post we’ve described some of the problems that are encountered when processing corporate filings from the SEC’s EDGAR database in XBRL. Today we present a system that overcomes these issues by downloading and processing XBRL filings on a daily basis, normalizing the financial data, computing common financial ratios, storing all data into a SQLite database, and then presenting the corporate reporting data for financial analysis through a mobile app for iOS, Android, and Windows Phone.
We are making all the sources for the data ingestion and normalization process available as Python scripts on GitHub under an Apache 2.0 license. The actual normalization rules as well as the financial ratios being computed are defined in external JSON files that can easily be modified without the need to edit the Python sources. In addition the MobileTogether Design file describing the mobile app is also available as open source in the same repository on GitHub so the mobile application can be easily customized as well to graph different data, show other financial ratios, or do more sophisticated financial analysis.
If you live in the 21st century and are not actually hiding underneath a rock or living in a cave, you probably are suffering from some form of information overload and feel overburdened by the number of things you have to do at any given moment in time. New information is constantly coming at you in the form of Twitter, Facebook, WhatsApp, text messages, or the latest social media app you installed on your smartphone, as well as good old radio, TV, newspapers, and magazines in their classic or digital versions, not to mention work or school email, personal email from friends and family, and all the social obligations from clubs, charities, and local community organizations.
So how do you actually manage to stay productive and deal with this onslaught of information without going crazy? How do you get things done, achieve your goals, and get to the mountaintop despite the constant head-wind?
Nothing interrupts the flow of development like waiting for a collection of files to transform – yet this step is unavoidable when writing, testing, and debugging XSLT and XQuery code. In addition to offering the XSL Speed Optimizer, we’ve worked hard over the years to make sure the processor in XMLSpy is as fast as possible. As quick as it is today, it’s still limited to a single core execution on the CPU in your development machine. Well, not any more.
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.
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.
The advantages of JSON as a lightweight, interoperable data format have secured its place as the favored mechanism for serializing and transporting data on the web. However, most applications still benefit from or require validation of client-submitted data. Enter the JSON Schema spec, which lets you describe the structure of JSON data for a particular application, for both documentation and validation purposes.
Though JSON Schema code is by design human-readable, building a complex schema with nested and repeating sections in a text-only editor becomes time consuming and error-prone quickly.
There are several reasons why an enterprise-grade, graphical JSON Schema editor is an asset for developers:
- Graphical view and intelligent entry helpers speed development
- Those new to JSON Schema can rapidly build a schema using the graphical view
- Allows incremental data modeling by which you generate a JSON Schema based on an existing JSON instance
- XML to JSON conversion makes it easy to move between formats as required
Let’s look at each of these ideas more closely and see how they’re implemented in XMLSpy.
We are excited to announce details of the latest release of Altova MissionKit desktop developer tools and server software products. Version 2016 includes full Windows 10 compatibility and updated relational database support across the product line, and it also introduces some new features that you simply will not find anywhere else.
XMLSpy 2016 includes the first full featured, enterprise-grade graphical JSON Schema editor. MapForce, our data integration tool, now includes a data mapping debugger that will revolutionize the way you define and test data mapping projects. Let’s take a closer look at these new features.
We’re pleased to announce the launch of the brand new and greatly improved Altova Online Shop.
It’s as convenient and secure as ever to purchase Altova software products, server license renewals, and support and maintenance (SMP) online. The first thing you’ll notice in the new shop is the redesigned, more modern UI that makes it easier to navigate, view your options, and request a quote. When you’re ready to purchase, the completely rebuilt back end will help process your order even more efficiently.
It’s also easier to navigate the upgrade process for products and support as well as annual server licenses, where you’ll have access to more flexible upgrade options.
We’re constantly striving to improve the purchasing experience for our customers and hope you’ll share any feedback or suggestions you have after visiting the Altova Online Shop in the comments below.