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The challenge of data quality and traceability is present in all organizations

In the age of digital transformation, all companies, whatever their size or sector of activity, need to pay particular attention to the quality, validity and traceability of their data and the business processes associated with it. That’s why Blueway’s Phoenix platform combines MDM (Master Data Management), BPM (Business Process Management) and ESB (Enterprise Services Bus).

Master Data Management projects respond to these specific needs, dictated by internal (product data, for example) or external (customer-supplier exchanges) demands of organizations, which can be classified into 2 main categories:

  • Improving data quality through a single repository
  • Traceability of data modifications and reconstitution of an up-to-date repository.

The benefits of Business Process Management solutions

The implementation of governance rules and the use of an MDM tool offer a global and coherent view of data, enabling a better understanding of its environment, the resolution of quality issues and the improvement of business performance thanks to reliable information.

MDM is the tool of choice for the Data Manager, the person responsible for ensuring data quality, integrity and consistency. An MDM solution provides the Data Manager with a robust infrastructure and processes for managing business-critical master data. This enables him or her to centralize information management, eliminate duplication, standardize values and deliver reliable, accurate data throughout the organization.


Improve decision-making and operational efficiency.


Reduce data errors and risks.


Promote cross-functional collaboration and integration between business applications.


Ensures compliance with current standards and regulations.


Improve customer satisfaction with accurate, up-to-date data to personalize interactions.

Put the odds in your favor for your MDM (Master Data Management) project

Aligning the identified needs with the repository construction stages requires a precise knowledge of the foundations of your “data and process” architecture.

To ensure the success of your project, you need to anticipate several points of attention, such as the ability to interact with other applications in your current and future information systems, data mapping and quality assurance, the life cycle of reference data, and regulatory requirements.

Source and target applications need to be identified, and the degree of confidence in the data quality of each software specified, in order to adapt information updates and consolidations, and the creation of master data. Similarly, the rules applying to the various fields, as well as the rules for managing and administering the repository, need to be defined upstream.

Based on these elements, you can define the main lines of implementation for your repository: purpose of the approach, complexity, granulometry, stability of the system over time, nature of the objects manipulated, efficiency indicators, interoperability with source and target applications… Your reference data will live and evolve continuously!

1st recommendation

Anticipating the architecture around the single database

Access to master data in the single repository is simplified by the automatic generation of WebServices, which guarantee the correct distribution of information and its use in the various “add”, “modify” and “delete” modes.

In this way, your single database architecture evolves towards a Service-Oriented Architecture (SOA), while respecting information access security rules.

You retain control of your data through management rules (field composition, length, mandatory character, RIB validation formula or INSE code, existence of code in a table, etc.), and your modifications are tracked and archived within the repository thanks to this approach.

2nd recommendation

Adapting the project to the corporate context and data acculturation

A good practice is to initially focus on less complex data entities before moving on to more critical ones. In any case, we recommend advancing in batches – for example, the supplier entity, then the product entity, then the customer – to facilitate governance and alignment at enterprise level on each perimeter. However, for each of these perimeters, the active involvement of all the internal teams concerned ensures that the vision is aligned with the reference data. Working in batches does not mean compartmentalizing the vision of data: customer service is not the only department to use customer data! This cross-functional vision of data is essential to the success of the project and its adoption. We also recommend jointly defining management and governance rules from the outset, to avoid errors and guarantee the reliability of information.

BPM : a new strategic priority for operations and top management
White paper : BPM

Choose Data Governance to support your Master Data strategy!

The Data Governance module is the Master Data Management foundation of our Phoenix data platform. With Data Governance functionalities, you can validate the chosen model, control data flows and reconstitute a unique repository to date. You can also produce corporate data presentation screens to facilitate access to reference information through user-friendly interfaces, accessible from any terminal (PC, mobile, etc.). Statistics can also be created.

Your management rules can be applied to all types of data: you define the attributes and targets to be associated with each piece of data to control, validate, transform or guarantee traceability.

Our strengths in deploying your master data governance


Management of different environments, applications and servers, adaptable and scalable data model.

Security and governance

Authorization and access management, management rules, automatic error checking, declaration of event elements (triggers).


Access to directories, business applications and standard application connectors, application mapping and impact analysis.

Data life cycle

Documentation, revision management and versioning, rebuilding repositories to date.


Data quality indicators and dashboards to analyze all aspects of your data assets.

… and beyond support your data strategy with the Phoenix platform

In addition to Phoenix’s MDM capabilities, our Data Platform also integrates BPM, ESB (Enterprise Service Bus), APIM and data catalog tools. It enables you to rapidly set up a single data repository to improve the quality of all your corporate data, and also to understand all the dimensions surrounding data flows within your organization.

The Phoenix platform supports your data governance strategy, making it agile and easy to implement. Our approach is simple and pragmatic, for rapid implementation!

Data Platform Phoenix : DQM, MDM, BPM, ESB, Data Catalog
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