Data
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Data Lifecycle Management

Le 04 December 2022

Data Lifecycle Management – DLM

Your Issues

Data is a strategic asset for organisations and economic players. Data lifecycle management (DLM) is thus becoming a key activity for stakeholders. We propose a rule-based approach to manage the data flow of an information system throughout its life cycle: from the creation and initial storage of the data to its deletion.

Data lifecycle management is thus an essential element in a data management strategy. It challenges the organisation’s cybersecurity and data confidentiality procedures, and hence its IS architecture.

In particular, DLM products automate processes, typically organising data into separate tiers according to specified rules and automating the migration of data from one tier to another. Typically, new data and data that needs to be accessed most frequently is stored on faster but more expensive storage media, while less critical data is stored on cheaper but slower media.

 

Our Offers

Business at Work offers a catalogue of services that meet the challenges of digital transformation and make your IT system more agile. In addition, to the development of a roadmap and a data lifecycle management trajectory, we can support you in the following areas

  • Audit of the organisation and processes for managing the data life cycle (properties, updating, compliance, quality)
  • Audit of architectures, in order to identify areas for improvement, in order to deport information of low transactional value and rarely consulted to storage
  • Security and confidentiality approaches
  • Design of storage and archiving solutions adapted to each context

 

Our strengths

A consulting offer specifically dedicated to the analysis and optimisation of analytical tools and databases :

  • Phase 1 – Flash Audit : a rapid, tool-based, exhaustive approach that maps all existing tools and data sources
  • Phase 2 – Analysis of the scope of the projects and launch of the optimisation and reduction phases of the budgets and schedules, in data processing

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