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Stellar Tech Connections

Data

Data your leaders can rely on, owned by someone.

We set the strategy and governance that make data trustworthy: clear ownership, agreed definitions, quality standards and policies that fit how your business actually operates.
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At a glance

Best for
Organisations where reports disagree, ownership is unclear, or regulators ask questions the data cannot answer
Typical engagement
Fixed-scope or ongoing, agreed to fit the work.
Typical duration
Varies by scope; agreed at the start of the engagement.
Team
Sized to the scope, drawn from our delivery team.
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The problem

Where this costs you time.

  • Conflicting definitions

    The same metric means different things to different teams.

  • No clear owner

    When a figure is wrong, nobody is accountable for fixing it.

  • Policies on paper only

    Rules exist, but they are not applied where the data is created.

What we do

Capabilities

  • Data strategy

    A direction for how data will support decisions and operations.

  • Ownership model

    Named data owners and stewards for each important data set.

  • Definitions and glossary

    Agreed meanings for core metrics, shared across teams.

  • Quality rules

    Standards for completeness, accuracy and timeliness, with checks.

  • Access and privacy policies

    Rules for who may see and change data, applied in the systems.

  • Governance operations

    Forums and processes that keep definitions and quality current.

Benefits

What changes when this works.

Outcomes we design for. Measured results appear only after a client confirms them.

  • One agreed meaning for each key metric
  • Clear accountability for data quality
  • Policies applied in the systems themselves
  • Confidence in reports and audits

Process

How data strategy & governance engagements run.

  1. Stage 1

    Discover and Diagnose

    Business, workforce and compliance analysis.

    Tech deliverablesProcess map, data-flow map, risk register

  2. Stage 2

    Design and Align

    Solution architecture, operating models, integration planning.

    Tech deliverablesArchitecture, prototype, test plan

  3. Stage 3

    Implement and Enable

    Deployment, onboarding, system validation, change management.

    Tech deliverablesBuild, integrate, test, train

  4. Stage 4

    Govern and Optimize

    Continuous compliance monitoring, reporting, automation and enhancement.

    Tech deliverablesMonitor, support, improve

Technologies

Tools we would use.

  • Governance

    • Data catalogues
    • Business glossaries
    • Ownership registers
    • Data stewardship
    • Data lineage

  • Quality

    • Data profiling
    • Quality dashboards
    • Validation rules
    • Reconciliation checks
    • Issue tracking

  • Policy

    • Access policies
    • Retention schedules
    • Audit logging
    • Privacy impact assessments
    • Classification standards

Industries

Where this matters most.

  • Oil and gas

    Field, contractor and production data defined and owned across site and head office.

  • Pharmaceuticals

    Data integrity and traceability set out for regulated records and audits.

  • Chemicals and fertilizers

    Plant measurements and cost data defined so operations and finance agree.

Related

Where this connects.

All services

FAQ

Questions we hear.

Answers are drafted for review. Anything that needs a fact from Stellar is marked.

Not always. Ownership and definitions come first. Tools support the process once it is agreed.

Have a business challenge worth solving?

Tell us what you're trying to fix. An engineer will reply, not a form robot.

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