Introduction
CryspIQ® is an all-in-one Data Fabric solution that uses a patented data collection method to prepare enterprise data for analytics and AI.
A data fabric is both an architectural pattern and a set of best practices designed to unify, govern, and operationalise data across the organisation. This includes:
- Data integration
- Data quality
- Active metadata
- Master data management
- Data pipelines
- Data catalogues
- Orchestration
- Analytics
- Data operations
CryspIQ® is delivered as a Software as a Service (SaaS) platform and is founded on the core principles defined within the DAMA framework.
From siloed data to trusted insight
Traditional data environments are fragmented, difficult to navigate, and costly to maintain. Data is hard to find, quality is unclear, and teams spend more time interpreting data than using it.
CryspIQ® replaces this with an integrated, contextualised data layer where data is easy to discover, quality is measured at ingestion, and noise is removed by design—making data usable by everyone, not just specialists.
Siloed, Isolated Data
- Hard to find ❌
- Difficult to use ❌
- Unknown data quality ❌
- High noise and duplication ❌
Integrated, Contextualised Data
- Easy to find ✅
- Simple to use ✅
- Measured data quality ✅
- Noise removed ✅
Overview
CryspIQ® is designed to simplify data preparation, deliver measurable business value, and make trusted data accessible across the organisation.
It enables teams to explore and use data without being constrained by technical interpretations or dependency on specialists. Any user can self-serve and ask analytical questions using natural, everyday language.
Standardise. Govern. Deliver.
CryspIQ® is built around three core steps that transform fragmented enterprise data into a trusted, AI-ready foundation.
These steps provide a clear, repeatable path from raw data to measurable business outcomes.
1) Standardise
Create a trusted enterprise model by decomposing and standardising source records once—so every downstream use case starts from consistent foundations.
Outcome: Consistent data structures, fewer transformations, and a reusable model for analytics and AI.
1. Standardise Your Data
CryspIQ® takes a fundamentally different approach to traditional data warehousing.
Elements of Ralph Kimball’s star schema and Bill Inmon’s Common Information Model (CIF) will feel familiar. CryspIQ® builds on the strengths of both methodologies to create a single, standardised enterprise data model optimised for modern analytics and AI.
By decomposing source records into a consistent, reusable structure, CryspIQ® eliminates the need for multiple downstream transformations. Once this method is embedded in your data strategy, end-to-end processes become consistent, repeatable, and far easier to manage.
The CryspIQ® methodology and universal context are technology-agnostic, meaning they can be applied across any cloud platform—AWS, Google Cloud, or Azure. CryspIQ® is delivered on Microsoft Azure to operationalise this approach securely and at scale.
2) Govern
Apply definitions, lineage, and access controls by design—so every dataset is defensible, traceable, and secure for enterprise use.
Outcome: Built-in governance for AI, audits, and the board—without adding tooling sprawl.
2. Govern Your Data
CryspIQ® embeds governance directly into the data layer—by design, not as an afterthought.
Using an intuitive interface, source systems are mapped into the universal context and enriched with contextual metadata at the point of ingestion. Business terms, definitions, lineage, and access controls are applied once and reused everywhere.
This approach ensures data is:
- Consistently defined
- Traceable end-to-end
- Secure at column and field level
- Ready for audit, compliance, and AI
The result is a living business glossary and governed data foundation that scales across teams without increasing operational overhead.
3) Deliver
Deliver trusted data for analytics, reporting, and AI at speed—so teams spend less time building pipelines and more time delivering outcomes.
Outcome: Faster time to value, lower operational overhead, and scalable self-service across teams.
3. Deliver Data at Speed
Once data is standardised and governed, CryspIQ® enables immediate delivery of insights across the organisation.
Users can ask questions of their data using plain, everyday language—no technical expertise or knowledge of source systems required. CryspIQ® automatically clusters related data types within a unified schema, making discovery and reuse simple and intuitive.
Data can be consumed through:
- Natural-language analytics
- Dashboards and reports
- Application-to-application workflows
- AI and machine learning pipelines
This allows teams to move faster, reduce dependency on specialists, and deliver analytics and AI outcomes with confidence.