By developing its Data Intelligence, the company aims to improve its efficiency by developing the knowledge and well-controlled sharing of its data.
KNOW, CONTROL AND SHARE YOUR DATA
It's a "Data As A Service" approach, designed to satisfy every need for useful business information in the most efficient way possible.
Data Intelligence requires a shared data culture, enabling everyone from business to IT to make the best use of their skills in a responsible collaboration that improves overall efficiency. In particular, Data Intelligence is the foundation of all forms of Business Intelligence. Without it, all information becomes suspect, and the frenetic need for information paves the way for the temptation of counter-productive “shadow IT”.
Data Intelligence rests on 4 essential pillars:
- Data Governance
- Data Architecture
- Data Management
- Data Platform
DATA GOVERNANCE TO SUPPORT YOUR TRANSFORMATION
Data Governance is the set of organizations, processes, roles and tools that enable us to achieve the goals of data intelligence: exposing data assets to power data products for business use.
It's a continuous process of adaptation and control, to ensure that our efforts serve the best possible performance for business teams, which then uses the right information for analysis, decision-making and action.
Since the key is to build a truly collaborative working relationship between business and IT, the definition of processes, roles and responsibilities, and the provision of resources and tools, are essential to support everyone's efforts towards continuous improvement.
As there is no absolute "best data governance", we can help you build and implement the one that's right for you today, in terms of objectives and resources, and continuously improve it, based on medium/long-term milestones.
ORGANIZE YOUR DATA
Data Architecture consists in representing and implementing the various logical and physical data models which, via the exposed Data Assets, feed a set of Data Products that must satisfy as many identified and relevant business needs.
To refine raw data into intelligible business models capable of delivering the quality of service expected by end-users, data architecture is an end-to-end vision of the path leading from raw data to its uses.
It involves integrating the logic of collection and ingestion, as well as the challenges of storing and making data available in the form of assets, with knowledge of the technical architecture components on which these flows will be based. Each new need expressed may give rise to a new asset or the modification/evolution of another.
The Data Architect is at the heart of end-to-end system documentation, and in particular of the data and transformation catalogs for which he or she is responsible, but also of Data Product portfolios and the identification matrices of governance players.
MAKE DATA GREAT AGAIN
Data Management is the implementation and management of data flows, transformations and storage formats that have been specified for business needs, and the provision of the various data assets.
All according to the standards established by the Data Architects, with the rigor of the DevOps trains of the IT production players, and the acceptance and functional control by the business contacts.
Whether the solutions used are logical or code-based, Data Management covers a wide spectrum of requirements linked to the quality of the service expected: data quality, production flow performance, compliance, rationalization of common assets, impeccable documentation of evolutions, traceability, versioning and data lineage for optimum transparency and maintainability.
Aware of the importance of this essential chain, we can help you identify the challenges involved, and provide support for implementation and governance.
BUILD YOUR DATA STACK
The Data Platform is the technical engine of your Data Intelligence. It includes all the software and infrastructure components required for the end-to-end transformation of raw data into information for business use.
It will of course include the storage spaces dedicated to the various stages of data qualification and refinement, as well as the connectors and active components for transport and transformation between these different states.
But the choice of this package must be consistent with two key elements:
- the quality of service expected from data provision, as performance, quality, security, compliance, documentation, etc.
- and the capacity for complementary integration with the existing information system, including its architecture, production, skills and budget constraints.
Because there is no absolute best platform, and the question of "cloud or no cloud" is far from being the only one, we offer you personalized support to balance technical requirements and costs..