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Product · Data Governance

Governance that makes AI
safe, fast and trusted

Every enterprise wants to ship AI faster — and every audit, every regulator and every hallucination is a reason to slow down. SCIKIQ dissolves that tension: it makes governance the thing that lets you move fast safely, unifying glossary, lineage, quality and compliance so every model, dashboard and agent runs on data you can prove is right.

3-phasegovernance framework
9 rolesbuilt-in RBAC
GDPRCCAR · BCBS ready
Book a live demo All modules
01Capabilities

Six foundations, one governed platform

Unify metadata, lineage, quality and compliance — and connect across business areas to prioritise risk.

Unified metadata & business glossary

Central definitions, ownership and usage context to align business and technical teams across your entire data estate.

Policy-as-code & templates

Reusable, version-controlled policies enforced automatically across all environments and data products.

End-to-end lineage & impact analysis

Trace data from source to dashboard and assess the downstream blast radius before any change is made.

Quality framework & trust scores

Rules, thresholds and SLAs with transparent scoring for AI-readiness and audit confidence, per dataset.

Privacy & compliance guardrails

PII and PHI masking, retention controls and consent tracking to meet GDPR, HIPAA and DPDP requirements.

Stewardship & role-based access

Clear ownership, approval workflows and least-privilege access controls enforced across all data domains.

SCIKIQ Control for automated data governance and quality: data stewardship, data quality management, metadata management, data lineage and an authoritative data source, radiating across data quality, data catalogue and data governance -- covering DQ rules, anomaly detection, data profiling, knowledge graphs, policy management and access controls.
Control SCIKIQ Control — data quality, catalogue and governance on auto-pilot, unified under active metadata management.
95%Reduction in compliance violations
80%Faster regulatory reporting
70%Reduction in data quality incidents
$12M+Avg. annual risk mitigation
02Data strategy

Governance starts with a data strategy

The module implements your data strategy end to end — strategic vision and scope, governance policies, standards and a target operating model — resting on four foundational pillars.

Information management strategy

Align the information strategy with business goals, and target the right level of maturity for each business unit.

Information ownership model

A collective ownership model that keeps decisions close to the business while centralising the analytics teams.

Enterprise data standards

Standardise what genuinely needs it — guided by real usage patterns — and stay flexible everywhere else.

Information quality

Joint IT and business ownership of quality, made transparent so teams trust the data and act on issues.

The building blocks of a SCIKIQ data strategy: data governance, architecture and data management; provisioning, consumption and strategic vision and scope; governance forums, a policies-standards-and-operating model, and data architecture.
Strategy The building blocks of an enterprise data strategy — from strategic vision through governance, provisioning and consumption.
03The anatomy

Three pillars, pre-configured out of the box

SCIKIQ ships with the whole governance module wired together — a Data Catalog, active Metadata Management and a robust Data Quality engine — with typical workflows for asset management, policy, cataloguing, discovery, PII detection, lineage and role-based access already in place, plus configurable regulatory frameworks such as GDPR, CCAR and BCBS.

The anatomy of SCIKIQ data governance: three pillars -- Data Catalog (catalog, domains, sub-domains); Meta Data Management (data discovery, information classification, glossary, lineage, access controls, relationship and knowledge graphs, PII detector, business data elements, profiling and EDA, policy management); and Data Quality (DQ rules, DQ dashboard, operational DQ dashboards, DQ management, data observatory, anomaly detection).
Anatomy One governance module, three pillars — catalogue, metadata and quality, each with its own toolset.
SCIKIQ metadata microservice architecture: metadata sources (Hive, Redshift, Postgres, RDBMS, column stores) flow through the Data Factory ingestion framework into Elasticsearch, MySQL and Neo4j, served by Search, Data Discovery and Frontend services, and delivered to hyperscaler databases, reporting, Data-as-a-Service and data products.
Metadata Active metadata on a microservice architecture — Data Factory ingestion, Elasticsearch search and a Neo4j knowledge graph.
04The framework

A business-led framework in three phases

Business leaders own their data domains and champion governance for their function. SCIKIQ turns that ownership into a repeatable, three-phase method — set up the structure, discover and understand, then share and deliver.

Set up the organisation structure

Model your organisation so the right information reaches the right team — then layer access on top.

Entities & departments

Mirror your legal-entity and org hierarchy — entities, business units and departments — so data and permissions segregate cleanly.

Domains, sub-domains & catalogues

Business-owned logical groupings of assets, each with a business and a technical owner kept accountable for keeping it current.

Authoritative Data Store

A single source of truth (ADS) per critical data element, with an authoritative access layer (ADAL) for the datasets that serve it.

Roles, groups & permissions

Nine built-in roles with RBAC plus row- and column-level access, each scoped per entity across every resource type.

A SCIKIQ entity hierarchy: ABC PLC with a group-level Head-Office and three legal entities -- ABC-NA, ABC-EU and ABC-APAC -- each containing Finance, Sales, Marketing and Ops departments.
Entities Mirror your legal-entity and department hierarchy — data and access segregate cleanly along it.
05Building blocks

From entity to data product

A shared vocabulary underpins the whole module. Every governed asset climbs the same hierarchy — from the top-level entity down to the data products your teams actually consume.

1EntityLicensing and top-level organisation construct — mirror your legal-entity hierarchy and segregate assets and access beneath it.
2Data DomainA business-owned logical grouping of assets by function or knowledge area, assigned to a catalogue with clear accountability.
3Sub-Data DomainA second level of organisation for deeper, business-specific hierarchies, each with its own business and technical owner.
4Data CatalogMetadata plus search at the intersection of departments and domains — where all physical resources and assets live.
5Data ResourceAny object of value: connections, tables, pipelines, models, datasets, reports, APIs, DQ rules and governance artefacts.
6Data AssetA trusted, approved resource with clearly defined ownership that has passed its qualification tests.
7Data ProductA self-contained value gateway — reports, Data-as-a-Service, Model-as-a-Service or intelligence services — built from assets.
A worked SCIKIQ hierarchy: Enterprise PLC branches into an Enterprise Catalog, Enterprise Domain and Company 1-3; Company 3 into Americas, APAC and UAE; APAC into a Sales Data Domain holding an APAC Sales Data Catalog of connections and data sets; with Master Data and Reference Data feeding customer, product, currency and country reference sets.
Catalog The hierarchy in practice — entities and companies resolve to catalogues where the physical connections and datasets live.
06Access & privacy

Least-privilege access, private by default

Nine predefined roles map cleanly to how data teams actually work. A user can hold several roles at once, each scoped to an entity, with role-based, row-level and column-level access on every resource type.

Client Admin

Full access and actions on every resource across SCIKIQ.

Entity Admin

Full access to all resources within a given entity.

Data Engineer

Creates connections and designs ETL jobs and related tasks.

Report Designer

Designs, publishes and shares reports and dashboards.

Orchestrator

Manages scheduled jobs across every kind of resource.

Data Analyst

Builds logical models, defines DQ rules and runs EDA.

Data Steward

Enforces governance policy and owns issue resolution.

CDO

Owns enterprise-wide data strategy, governance and policy.

Viewer

Sees only the published dashboards and reports they can access.

Built-in PII detection & treatment

The PII Detector and Analyzer finds sensitive data across databases and files, matching patterns such as:

  • Email
  • Phone
  • Passport
  • SSN / Tax ID
  • Credit card
  • Address & geo
  • Names
  • Maiden name
  • Social handles
  • Gender
  • Nationality
  • Religion
  • IP address
  • Org names

Then it treats what it finds — partial or full masking, tokenisation, randomisation or consistent hashing — so data stays usable but is no longer personal.

07Govern AI

Govern AI with confidence

Reduce hallucinations, speed up policy work and maintain end-to-end auditability — without adding overhead.

Mitigates AI hallucinations

Trusted, governed data flows into models, dramatically reducing unreliable outputs.

Generative AI assistance

Draft policies, build glossaries and generate audit packs using natural language — in minutes.

Knowledge graph & search

Elastic search across your metadata graph for faster discovery and impact analysis.

Audit-ready evidence trails

Auto-generated evidence packs continuously mapped to GDPR, HIPAA and DPDP.

Need to pass an audit and ship AI at the same time?

We would love to think through it with you — no pitch, no form maze.

Talk to us

Frequently asked questions

What does SCIKIQ Data Governance cover?

Six foundations: unified metadata and a business glossary, policy-as-code and templates, end-to-end lineage and impact analysis, a quality framework with trust scores, privacy and compliance guardrails, and stewardship with role-based access.

Is SCIKIQ's governance AI-powered?

Yes. SCIKIQ uses AI to assist metadata management, data quality and stewardship.

Does SCIKIQ help with privacy and GDPR compliance?

Yes. Built-in privacy and compliance guardrails support regulations such as GDPR.