Building Apps with an Intelligent Database Wizard


Data-driven solutions like database and enterprise apps rely on connection to, and interaction with, backend databases. Backend relational databases, however, store data in tables that reflect complex data relationships. This provides numerous advantages for effective data management and data integrity but can make it difficult to access and work with the data stored therein in new ways. App developers need to have a comprehensive understanding of database design principles and the SQL query language just to get started.

In contrast, real world data relationships most often represent parent-child relationships or even deeper hierarchical structure. As such, working with hierarchical data where relationships can be visualized in a tree structure can be much simpler and more flexible, leading to faster development. This approach is also more accessible to developers without extensive SQL expertise.

To make building apps that connect to the backend relational databases that are ubiquitous in today’s enterprise easier, faster, and available to a wider range of developers, Altova MobileTogether takes an entirely unique approach. Its visual Database Wizard lets developers easily build a query that returns hierarchical data, work with that data in the app, and then easily save the data back in hierarchical form, letting MobileTogether take care of normalizing the data and writing it back to the corresponding linked tables. Let’s take a look at how it works.

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Role-based Access Control in Enterprise Apps


Enterprise database apps are increasing in prevalence due to their advantages for enabling access to—and easy management of—the ever-growing amount of critical data business users need to work with on a day-to-day basis. Unlike other types of business productivity apps, database apps must include measures for managing different levels of user access to maintain the security and integrity of the enterprise data they expose.

This can include managing read-only and editing access rights or restrictions on access to certain types of data. While it is essential to ensure that only authorized personnel have access to confidential data, levels of permissions often vary throughout an organization. Apps built using Altova RecordsManager include comprehensive tools for managing role-based access to database data that can reflect these complicated relationships that exist within an organization.

Let’s take a look at how RecordsManager makes it easy for app administrators to manage complex role-based permissions with visual tools.

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Getting Started with Altova RecordsManager


RecordsManager is a new tool from Altova to build business database solutions in record time using a powerful visual design interface. RecordsManager is a free, pre-built MobileTogether solution that is automatically available when you install MobileTogether Designer. The pre-built solution includes sample data sets, and the MobileTogether Simulator previews execution of the database solution right inside the free to use MobileTogether Designer. Getting started with Altova RecordsManager is just one click away when you launch the Designer. Soon you will be building your own custom database apps without needing backend development or manual coding.

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Build No-Code Database Apps with RecordsManager


We are excited to announce availability of a new product in the Altova app development framework: RecordsManager.

Altova RecordsManager offers a completely visual, no-code interface for quickly creating custom database apps. RecordsManager is perfect for any app that handles data in records: think contract management, a customer database, an invoicing system, a database of local attractions or collections – the sky is the limit.

Your RecordsManager app will automatically be available on desktop devices as well as on mobile using native iOS and Android apps and provides tons of features that make it easy for end-users. Let’s see how it works.

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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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MapForce Data Mapping Tutorial (Video)


Altova MapForce is an any-to-any data transformation, conversion, and ETL tool for integrating data.

A graphical data mapping tool, MapForce has an intuitive drag-and-drop interface that lets you easily convert data between any two formats, such as XML, JSON, relational databases, NoSQL databases, EDI, and more. It also features an extensive library of conversion functions that can be chained together to form custom functions that can be reused throughout your projects.

Data translated by MapForce can be pulled to or pushed from a relational or NoSQL database and all data management products, and it can be adapted to customize in-house data management solutions.

The MapForce tutorial video below covers all major features offered by the data integration tool and shows example mappings between several different types of files.

You can try MapForce yourself with a free, 30-day trial.

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Transforming and Converting Protobuf


MapForce supports mapping protocol buffers (Protobuf) to and from other structured data formats as mapping sources or targets. In the constant quest for more efficient ways to transfer, manipulate, and manage large structured data sets, Google has created a language- and platform-neutral data format similar to XML, but smaller, faster, and simpler than even JSON data. Tools are available to generate and work with Protobuf using Java, Python, C++, C#, Ruby, and other programming languages.

The structure of any Protobuf message is defined in a .proto file that defines each field name and value type. Altova MapForce lets users drop these .proto files into a data mapping as a source or target along with any other data, including XML, JSON, relational databases, Excel, flat files, REST and SOAP web services, and others.  .proto files versions 2 and 3 are supported.

A MapForce data mapping creates compatibility between existing XML, JSON, database or legacy data formats and new applications leveraging the efficiency of Protobuf.

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