As already mentioned in a previous post about enterprise data management,
Information reveals data as the most valuable asset of an organization. It has the power to make your business unique.
To do their work on a daily basis, the « business » stakeholders rely on data. These are also the basis of decision-making for the company managers. However, the unavailability of the data results in an immediate operating loss, the financial amount of which may be very significant. In other words, data is a vital resource for the proper functioning of the enterprise.
We can therefore identify 3 main principles that are inseparable from data management :
Understand in order to ACT
Data and access to them form an « ecosystem » of which it is essential to understand the interactions at the risk of weakening or even destroying the balance in computer applications. This approach is the only one that guarantees the harmonious maintenance of data and programs, whatever the field of activity of the company : finance, insurance, industry, administration, trade, service...
To this effect, the solution is to systematically integrate functionalities in order to understand the existing. When required, the level of this understanding before intervention goes from the simple identification of the data role in the ecosystem to the comprehensive inventory of all interactions between programs and data. Taking into account the « programs-data » interactions, it will especially allow the joint agility of programs and data to meet the needs of application evolution.
Master in order to PROTECT
The « technical » interventions (development, maintenance, migration, extraction…) all present, to varying degrees, « data » risks which can be classified in three main categories :
- the regulatory risks : privacy, Bâle II, Sarbane & Oaxley, GDPR… Failure to comply with those rules may lead to the criminal responsibility of the entrepreneur, who may be financially sanctioned with fines.
- the risks associated with data loss : the forgetting of data is by definition difficult to timely identify and the reconstruction costs can subsequently become colossal.
- the risks associated with inconsistencies cause malfunctions in the enterprise and their costs are complex to measure, their consequences are often unexpected for the enterprise but also for the clients, providers or further partners.
To cut the data risks, you have to :
- trace the data and their uses by the programs
- protect the data confidentiality
- compare data before and after any interventions : these comparisons allow you to make sure that every data concerned by the intervention is properly treated on the one hand, and that the initial data consistency has been correctly maintained during the intervention on the other hand.
Optimize in order to WIN
The triple aspect « agility, industrialization, security » allows you to complete your projects on time and on budget :
- by reducing workloads
- by diminishing the completion deadlines
- by guaranteeing the conformity of the intended results
The essential contributions of this solution are, among other things :
- an increase of the quality of the Information Systems.
- a drastic reduction of the number of « data » malfunctions and cost thereof.
Rever is the spin-off of a university-based database engineering laboratory. Specializing in data sustainability, their portfolio of customized software and services is designed to optimize the value of data for organizations.