Any Data, On-demand
The simplest, most economical and robust platform to convert your IT landscape into a “dynamic virtual layer”. Up to 80% more cost-effective.
Virtual Layer
The future of Data Virtualization.
r4apps harmonizes disparate data sources without changing the underlying source data. This allows you to make this data available to be used in processing, decision making, AI and analysis in real time.
Data in Real-time
Up to 5x quicker with reusable virtual modules that can be included in any process step, or orchestrated into a new process.
Highly Interoperable
Select only the data you need when you need it, from any source. Easily combine it with the most modern tools and intelligence.
Modular & Composable
Combine modules from any aspect of your IT landscape in a modular and composable way. Create and modify these modules “on the fly” with no code by fusion teams.
One comprehensive tool, no-code solution
Our virtual layer offer is the one-stop solution that will give you everything you need and want. For example, restructure your organization and reporting without changing any of the underlying structures and data.
FAQs
Which objects to migrate and how?
You may not fully anticipate what objects need to be migrated (structures, processes, data objects, etc.) and this detail is often not known until you are actually in the migration, i.e., you don’t know what you don’t know. This is where r4apps excels – allowing you to identify and transform data on the fly, as you work, live. Even if there are hundreds of millions of records. This can save you up to 80% of the effort and budget for data migration.
How to ensure only good data is pushed to the new system?
r4apps easily prepares the data that’s always hard to deal with – the client-specific elements (e.g., cost centres, materials, projects, etc). r4apps effectively leverage AI and other analytics to identify and deal with duplicates, missing and non-compliant data, etc. by creating a virtual layer from all existing data sources that are easily understood, auditable and agile. Savings of over 50% are common.
How to deal with complex data transformation?
Complex data transformation e.g., with multiple dependencies, no 1:1 mapping, or transforming to a moving target can absorb over 70% of the budget. r4apps “works by doing” so avoids concept phases and extensive re-work saving up to 75% in time and budget
