01
What do users need to discover?
Identify the datasets, models, metrics and definitions that create the greatest friction when they are difficult to locate or interpret.
Data Management
Data Catalog
Support people find trusted data without depending on institutional memory or private spreadsheets.
NoèmeX works with organizations to design cataloguing approaches that make enterprise data easier to discover and understand. A useful catalog does more than list tables: it connects assets to business definitions, owners, quality status, source systems, lineage and approved use.
The work starts with the information people actually need to find and trust, then defines the metadata, governance and operating processes required to keep the catalog current.
NoèmeX perspectiveMake the system intelligible first: reveal the structure, constraints and variables that determine where change can produce the intended outcome.
Related leadership priorities
Data priorities change with the decision the organization needs to trust.
Use these pathways to connect data foundations to governance, technology, AI readiness and executive decision-making.
Questions we address
The decisions that shape the data catalog work
We frame the engagement around the business, governance and technical questions that must be resolved for the capability to work reliably at enterprise scale.
02
What makes a catalog entry trustworthy?
Define the ownership, certification, quality and context signals that distinguish approved assets from merely available ones.
03
How should cataloguing fit existing workflows?
Connect catalog maintenance to governance, modeling, onboarding and change processes so metadata does not become stale.
04
How should access and discovery work together?
Allow users to understand what exists and how to request or use it without weakening security controls.
What we deliver
A practical structure that can move into implementation
The exact scope depends on the organization, but the work typically produces a combination of these outputs.
01
Catalog use-case assessment
Priority personas, discovery journeys and high-value assets that should be catalogued first.
02
Catalog information model
The metadata, ownership, certification, quality, lineage and usage fields attached to each asset.
03
Classification and taxonomy
Business domains, categories, tags and naming conventions that make assets easier to browse and search.
04
Certification workflow
A repeatable process for reviewing, approving and marking trusted enterprise data assets.
05
Access request integration
A design for connecting discovery with governed access and approval processes.
06
Catalog rollout roadmap
A staged adoption plan that starts with priority domains and expands as metadata and governance maturity grows.
Selected work
Evidence from a real enterprise data environment
This example is drawn from the documented Global Data & BI case-study portfolio and illustrates the operating conditions behind the service.
Data discovery challengeThousandsChemical industry · Enterprise data discovery
Global data governance platform
The global governance case describes thousands of spreadsheets, locally stored models and fragmented documentation across a 70-country enterprise. The transformation centralized governance workflows and model information, demonstrating the scale of the discovery and context problem that a formal enterprise catalog is intended to address.
Read the case studyRelated data services
Continue into the adjacent data capability.
These services often intersect in the same transformation program, but each has a distinct purpose and page.
How we work
Use the engagement model that fits the data problem.
Data work can begin as focused advisory and continue into project delivery, embedded support or an ongoing managed model.
Advisory
Focused support for assessment, governance, architecture and roadmap decisions before major implementation commitments are made.
Read more →Project delivery
Structured implementation when the data design needs to move into engineering, migration, rollout and adoption.
Read more →Embedded teams
Specialists working alongside internal teams when continuity, production support and ongoing improvement matter.
Read more →Your Contact Persons
Connect directly with the people responsible for this work. Explore their experience and contact options.
Zahra Fathisalout
Founder · Eng., CSP, CMLAI
Corporate governance · ASC-C.Dir. candidate
Works across strategy, enterprise transformation, data, AI and governance, bringing operational engineering experience to complex transformation decisions.
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Brendan Young
B.Com, Director of Operations
Connects transformation design with operating discipline, drawing on logistics, fulfillment and high-throughput operational leadership.
View profile →
Data Catalog
Start with the data problem that is creating friction.
Share the business process, systems involved, current data constraints and the decision or operational outcome that needs to improve. Our teams can determine where the work should begin and how it connects to the wider data estate.