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The positive impact of digitalization in asset rich Enterprises is getting more and more recognized globally — reduced costs, improved operational efficiency and greater productivity. New techniques and softwares open up for new and advanced solutions and great technical achievements.

But despite these huge technical improvements, it is very common that enterprises need to work with files within their digitisation projects. How is it possible that in 2022 Enterprises still need to deal with files?

According to recent studies, Enterprises use over 800 applications for their operations today (MuleSoft Connectivity Benchmark 2022). The large number of applications creates an integration challenge, especially as many older legacy systems don’t have available API’s. However, many legacy systems can export and import files which opens up opportunities to integrate and automate workflows across systems. 

The most common use cases considering automated files handling could be grouped into two main categories:

  1. Files to Database or API. Collect files from a local storage or a remote storage, pull in the data, interpret it and send it to another system for further processing.
  2. File Management. Collect and move files from multiple distributed locations and archive them in a central location or files saved locally that need to be renamed and organized in a different location.

Challenges with automated files handling

Files handling from a traditional IT and automation perspective is often considered time consuming and difficult to manage. Data cleaning, data transformation, checking for updates, mapping data, converting files formats and setting up data communication (pipelines and flows), takes time to develop, and is challenging to maintain.

Simplify processing of file-based data with pre-built modules

The main advantages of using low-code tools like Crosser is that once the data is inside the platform all other standard tools can be applied. The data can be:

  • Cleaned-up: Remove invalid data points, fill-in missing data, smooth sensor data etc.
  • Transformed: Change data structures, add metadata etc.
  • Filtered: Apply conditions, based on data.
  • Processed: Apply filters, triggers to other systems, custom algorithms or ML models.

Files as input and output for Machine Learning

In some cases files can be used as input and output. For example, you can pick the data from an FTP server, then process through a Machine Learning model and then the result is delivered to another FTP server.

 

Crosser Intelligent Integration Low Code Concept Sketch

 

Why use a tool like Crosser?

There are several reasons why a tool like Crosser could be used for automating files handling for global Enterprises:

Low-code Functionality

Low-code solution with library of pre-built modules that enables different functionalities that you typically need to implement the use cases mentioned above. The modules are combined with a very visual design tool to create your specific use cases.

Hybrid architecture

Clear separation between:

  • Crosser Control Cloud: The management tool which is running as a cloud service and you can access with your web-browser, here you can find the design tools.
  • Crosser Node: The execution environment where you run the use cases or flows, you choose where you want to install this environment. It can be run locally inside your firewall, giving you access to systems that are not accessible from the internet. 

Typically it is installed close to the data source like the factory floor, a data center or the cloud. The execution environment is generic and can host any kind of use case, giving you the flexibility to add different use cases after being deployed.

 

Crosser Intelligent Integration Centralised Management

 

Centralized Management

Central Management and Enterprise Grade Governance, all communication between these execution environments and the Crosser Cloud service is always initiated from the distributed environment back to the cloud services. You don’t need to expose the internal environment for traffic from the public internet.

When to use Crosser?

Intelligent Integration in all 4 layers (cloud, enterprise on-premise, site and edge) is relevant for Industrial businesses and asset rich organizations.

Crosser is used to cover a broad spectrum of integration applications: 

  • Cloud Integration. Integrate any Cloud Provider or SaaS application. Hosted on own infrastructure or Hosted Flows by Crosser.
  • Enterprise Integration. Integration between the operational systems, ERP systems, supply chain and other enterprise systems.
  • Site/Factory Floor. Intelligent Integration of all factory data. Systems or machine data (IoT).
  • Edge. Remote analytics and integration of edge data. Sensors, computer vision, APIs.

Integrations can be built at one horizontal layer or you can build integrations across the technology stack. All of this is enabled through the modules provided in the library, and the unique ability of the Crosser runtime (node) to be deployed at all four levels, this is the key functionality that the Crosser Platform offers.

One key feature - Test with real data

One very appreciated feature within the Crosser platform is the ability to test your intelligent integrations with real data, from your real data sources, before deploying in production. The remote testing feature secures the success of your project, by radically simplifying the verification integration functionality and value.

Interested in knowing more about automated files handling and/or the Crosser platform?

See the whole webinar (free registration) How to Automate Data Files Handling for Asset Rich Enterprises here →

Or, contact us for a free live demo here →

About the author

Johan Jonzon | CMO

CMO & Co-founder

Johan has 15 years background working with marketing in all possible type of projects. A true entrepreneurial spirit operating between strategic and hands-on details. He leads our marketing efforts as well as the product UI design.

Sales and market-oriented with a focus on getting the job done. He has worked with web and communication in Sweden and internationally since 1999. Since 2012, Johan has been focusing on real-time communication, and the business and operational benefits that comes with analyzing streaming data close to the data sources.

I want everything we do to be clean, simple and very, very user-friendly. We strive to be the clear leader in usability among our peers.

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