Compliance is a global problem. Different parts of your organization have different systems, built on different technologies, of different ages. r4apps gives you access to information on all of those systems—without causing disruption to existing systems—in one place.
The time and resource cost of extracting, transforming and loading data into new data repositories is prohibitive. The data is out of date as soon as you do it. r4apps leaves your compliance data where it is and instead gives you live access to harmonised data.
Looking for compliance failures is like detective work. Once you get a hint, you need to dig deeper and look from different viewpoints in order to really understand what’s going on. r4apps allows business people to work naturally in order to evolve answers in complex company information.
r4apps enable business people to create comprehensive views across disparate data sources and to design and build automated compliance monitoring processes with fully automated solutions using up-to-date business information, saving at least 80% over traditional IT-led approaches.
r4apps consulting will support your compliance monitoring PoC project with its exceptional business and data analytics skills, without the need to secure IT support or funding, and 80% faster with fewer resources than traditional approaches.
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.
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 leverages 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’s easily understood, auditable and agile. Savings of over 50% are common.
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 of up to 75% in time and budget.
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