Bidatia

SERVICES

Data governance

We manage data as an asset: we audit it, set its rules and leave it ready to use. And we leave a committee, roles, rules and metrics running, with AlmIA monitoring data loads every day.

Tell us about your projectHow we do it

Official partner erwin by Quest

Does any of this sound familiar?

  • Nobody is accountable for the data

    When a figure is wrong, nobody knows who should fix it or which system it comes from.

  • One concept, several definitions

    “Active customer” means something different in every report and every department.

  • Regulation and audits

    GDPR, Spain's ENS or the EU AI Act require you to know what data you hold, where, and who accesses it.

HOW WE HELP

What we help you solve with this service

Making the most of company knowledge

«Information is scattered across documents, emails, people and systems.»

  1. Assistants that answer with your documentation and cite the source.
  2. They respect each person's permissions and log every answer.
  3. Where your team already works: Teams, the website or WhatsApp.
Related servicesAI automation

Strategic reporting

«We need a complete view of the operation, not twenty separate reports.»

  1. We define a balanced scorecard with management: objectives, indicators and owners for each area.
  2. We bring data from across the operation into a single, governed and reliable model.
  3. Ready to be exploited with AI: natural-language questions, alerts and root-cause analysis.
Related servicesData and analyticsData platforms

Reducing licences

«We pay for too many BI licences. Can we move our dashboards to a web application?»

  1. We analyse your current dashboards: data sources, metrics and features.
  2. We run a proof of concept with real data.
  3. We migrate the dashboards in waves, starting with the quick wins.
  4. We put governance in place and train the teams.
Related servicesData and analyticsAI-powered development

Improving data quality and trust

«Our data has errors and inconsistencies, or we don't know which information is reliable.»

  1. Quality rules and indicators on critical data.
  2. A source of authority for each master data entity: customers, suppliers, products.
  3. Daily monitoring of data loads to catch failures before the business does.
ProductsAlmIA

Governing data and AI

«We need control over data, agents, access, policies, traceability and the use of AI.»

  1. Roles, a committee and data and AI usage policies that are actually applied.
  2. Catalogue, lineage and a register of the AI systems in use.
  3. Compliance with GDPR, Spain's ENS and the EU AI Act.
Related servicesDigital strategy

DATA GOVERNANCE

What we do

  • Kick-off and assessment

    Data maturity audit following UNE 0080, data and flow map, and applicable regulation.

  • Organisational model

    Domains, data owners, stewards and custodians, a governance committee and a data office.

  • Catalogue, glossary and lineage

    Technical and business dictionary, centralised metadata and lineage back to source.

  • Data quality

    Rules by dimension, quality indicators with thresholds and an incident workflow.

  • Master data

    Sources of authority for each entity, with criteria, owners and life cycle.

  • Publishing and self-service

    Internal data marketplace, data products and access agreements.

How we do it

  1. Assessment

    Maturity following UNE 0080, inventory of critical assets and priorities.

  2. Model and roles

    Domains, owners, committee and minimum approved policies.

  3. Tool and catalogue

    Tool implementation and onboarding of the first domains with glossary and lineage.

  4. Quality up and running

    Rules, indicators and alerts, with AlmIA monitoring data loads every day.

Illustrative mock-up

What you get

  • Maturity report and governance roadmap
  • Organisational model with roles and committee
  • Catalogue, glossary and lineage for the priority domains
  • Quality rules and indicators with a dashboard
  • Data and AI usage policies

What it brings to each role

Confidence in the figures, clear owners and a model that supports AI and audits.

Technology

  • Microsoft Purview
  • OpenMetadata
  • Anjana Data
  • erwin by Quest
  • Collibra
  • Informatica
  • Great Expectations
  • AlmIA
  • DAMA-DMBOK
  • UNE 0077-0080

Related technologies

OUR PRODUCT

From policy document to daily control with AlmIA

AlmIA monitors data loads on Microsoft Fabric, translates every run into a business status, diagnoses errors and lets you relaunch without opening Fabric. Everything goes through a gateway installed in your network, which keeps your credentials and your data.

See AlmIA

Related case studies

See all case studies

  • Large local authority with its own data office

    Selecting the data and AI governance tool

    Challenge
    From among the leading data governance tools on the market, the one that best fitted the client had to be selected to govern BigQuery and the dashboards, and to integrate the data governance tools available in the cloud.
    Solution
    Maturity assessment, requirements catalogue and weighted scoring matrix; ten tools evaluated with the vendors and cross-checked with Microsoft, Google and Anjana.
    Result
    Three finalists and a reasoned decision, reusable criteria, and compliance assessed against UNE 0077-0080, UNE 0085 and the EU AI Act.
    Data governance

  • Several ministries of Spain's central government

    Common criteria for choosing a data governance tool

    Challenge
    Data governance initiatives running in parallel across different ministries, with no common criteria for choosing a tool and the requirement to fit public administration regulations.
    Solution
    Gathering of functional and technical requirements for each ministry, comparison of the tools on the market, open-source ones included, assessment of data maturity against the UNE standards and a recommendation for each usage scenario. Theoretical and hands-on training on real cases, and support during roll-out.
    Result
    A decision backed by consistent criteria reusable across ministries, and a basis for starting implementation without redoing the analysis.
    Data governance

  • Public body managing data from more than 200 organisations

    Purview and automatic documentation with AI

    Challenge
    Fabric, SQL Server, AWS S3 and Purview coexisting, unmonitored loads, no guaranteed quality, and knowledge concentrated in suppliers that was lost with every turnover.
    Solution
    Maturity audit and target organisational model, phased roadmap, Purview with domains, data products and glossary, and AI accelerators to document the models.
    Result
    Documentation generated automatically with minimal supervision, owners and roles identified, a two-year roadmap and a self-sufficient technical team.
    Data governance

  • Bank

    Data governance and information architecture

    Challenge
    More than 60,000 tables neither classified nor organised by subject area, with no catalogue accessible to the business and no common modelling criteria.
    Solution
    Classification by subject area with erwin Data Modeler, a catalogue for business and technical users, an architecture review and a methodological framework based on DAMA and Kimball.
    Result
    A governance methodology applicable to every platform, data the business can understand, and modelling defects identified.
    Data governance

  • Regional cybersecurity agency

    A data governance model with a first data domain and product

    Challenge
    Many data sources at different levels of maturity and an architecture not designed to govern them: no shared view of what data existed, who was accountable for it and how to use it with confidence.
    Solution
    Assessment of the maturity of the data sources and of the existing architecture, gap analysis, design of the architecture supporting data governance, and roll-out of the model with a first data domain and product.
    Result
    A data governance model in place, prioritised gaps and a working data product that serves as the pattern for the next domains.
    Data governance

  • Spanish central government ministry

    Data governance training and OpenMetadata roll-out

    Challenge
    Technical and business teams had to take on data governance without a shared set of concepts or a catalogue tool in place.
    Solution
    Training sessions for technical and business teams on data governance methodology and techniques, and roll-out of OpenMetadata as the catalogue.
    Result
    Teams sharing the same data governance language and criteria, and a working open-source catalogue to build on.
    Data governance

FAQ

Frequently asked questions

Straight answers to what we're asked most.

Which data governance tools do you implement?

Microsoft Purview, OpenMetadata, Anjana Data, erwin by Quest, Collibra and Informatica. We choose based on your ecosystem and budget.

How are data governance and AI related?

An AI is only as reliable as the data it uses. Governance defines which data is correct, who is accountable for it and where it comes from; and AlmIA checks every day that the loads producing it run and arrive on time.

Do all data have to be governed at once?

No. You start with the critical domains and data (those used by leadership, AI or regulators) and expand in phases.

Which standards do you follow?

DAMA-DMBOK and the UNE specifications 0077 (governance), 0078 (management), 0079 (quality) and 0080 (maturity).

Shall we talk about your project?

A first 30-minute conversation, no strings attached.

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