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Enigma IT Solutions

Services

Five connected disciplines

From source systems to confident decisions. Engage us for one discipline, or bring them together in a single programme.

Business analytics

Are we measuring the right things?

Connect data to the objectives that matter, so leaders can see what is happening, understand why, and decide what to do next.

Discuss your performance framework

The business problem

Many organisations have more reports than ever, yet still struggle to answer basic questions about performance. Measures are defined differently across departments, priorities compete for attention, and analysis often starts from the data that happens to be available rather than the decisions that need to be made.

How we approach it

  1. 01We start with the decisions your people need to make, then work back to the measures and data that support them.
  2. 02We run structured workshops with business and technical stakeholders to agree definitions, owners and priorities.
  3. 03We translate findings into a practical roadmap, so analytics investment is sequenced around business value rather than technology for its own sake.

What we deliver

  • Business requirements analysis
  • KPI and performance-framework design
  • Operational and financial analysis
  • Process and performance insights
  • Data-driven decision support
  • Analytics strategy and roadmaps
  • Stakeholder workshops
  • Use-case identification and prioritisation

The value to you

  • A shared, documented understanding of how performance is measured
  • Analytics effort focused on the questions with the greatest business impact
  • Clearer accountability for each measure and its underlying data
  • A realistic plan that business and technical teams both support

Typical deliverables

  • Requirements and decision-mapping documentation
  • KPI framework with definitions, owners and calculation rules
  • Prioritised use-case backlog
  • Analytics roadmap
  • Workshop outputs and findings summary

Situations where this helps

  • Defining a consistent set of executive KPIs across business units
  • Identifying where operational delays are affecting customer outcomes
  • Prioritising which analytics projects to fund in the next financial year

Data analytics

What is the data actually telling us?

Turn raw data into findings people can act on, with analysis that is rigorous, explained clearly and tied to a recommendation.

Talk to us about an analysis

The business problem

Data often holds answers that never reach decision-makers. Analysis can stall in spreadsheets, be difficult to reproduce, or arrive as charts without a clear conclusion. When findings are hard to interpret, they are easy to ignore.

How we approach it

  1. 01We profile the data first, so everyone understands its completeness, accuracy and limits before conclusions are drawn.
  2. 02We choose methods that suit the question, from straightforward trend analysis to statistical and predictive models where they are justified.
  3. 03We present results in plain language, with the evidence, the confidence level and the recommended action set out together.

What we deliver

  • Exploratory data analysis
  • Diagnostic and trend analysis
  • Customer and operational analytics
  • Financial and performance analysis
  • Forecasting and predictive analytics
  • Data profiling
  • Statistical analysis
  • Custom analytical models
  • Insight presentation and interpretation

The value to you

  • Decisions supported by evidence rather than assumption
  • Early visibility of trends, risks and opportunities
  • Repeatable analysis that can be refreshed as new data arrives
  • Findings that non-specialists can understand and act on

Typical deliverables

  • Data profiling and quality assessment
  • Analytical findings report with recommendations
  • Reusable analytical models or notebooks
  • Forecasts with documented assumptions
  • Executive presentation of results

Situations where this helps

  • Understanding the drivers behind changes in customer retention
  • Forecasting demand to support stock or staffing decisions
  • Analysing cost trends to find where spending can be controlled

Data engineering

Can we rely on the data arriving on time and correct?

Design and build dependable pipelines and platforms that move, clean and organise data, in the cloud, on-premises or across both.

Plan your data platform

The business problem

Reporting and analytics are only as reliable as the data feeding them. Manual extracts, fragile scripts and undocumented integrations create delays, errors and risk. As data volumes grow and systems change, these weaknesses become harder and more expensive to manage.

How we approach it

  1. 01We assess your current sources, integrations and constraints before recommending a platform or pattern.
  2. 02We build pipelines with validation, logging and monitoring included from the start, so issues are found before they reach a report.
  3. 03We document what we build and hand it over in a form your team can operate, extend and support.

What we deliver

  • Data ingestion and integration
  • ETL and ELT pipelines
  • Data transformation and orchestration
  • Data warehouses, lakes and lakehouses
  • Cloud data-platform implementation
  • On-premises data solutions
  • Hybrid data integration
  • API and third-party system integration
  • Pipeline monitoring and optimisation
  • Data quality and validation controls
  • Platform migration and modernisation

The value to you

  • Timely, consistent data without repetitive manual effort
  • Fewer errors reaching reports and decision-makers
  • A platform that can grow with data volumes and new sources
  • Lower operational risk through monitoring and documentation

Typical deliverables

  • Source-system and integration inventory
  • Data pipelines with automated validation
  • Data warehouse, lake or lakehouse implementation
  • Monitoring, alerting and run documentation
  • Migration plan and cut-over support

Situations where this helps

  • Replacing manual spreadsheet consolidation with scheduled, validated loads
  • Bringing ERP, CRM and operational system data into one governed platform
  • Moving an ageing on-premises warehouse to a modern cloud or hybrid platform

Data architecture

Will our data environment still work as we grow?

Create a structured, scalable foundation for trustworthy data, with clear models, integration patterns, governance and security.

Review your data architecture

The business problem

Data environments often grow one project at a time. Without an overall design, the result is duplicated data, conflicting definitions, unclear ownership and platforms that are difficult to secure or change. Each new requirement takes longer than the last.

How we approach it

  1. 01We document the current state honestly, including the strengths worth keeping.
  2. 02We design a target state that reflects your strategy, risk appetite, skills and budget, not an idealised reference model.
  3. 03We set out a staged roadmap, so the architecture improves through practical steps rather than a single large change.

What we deliver

  • Current-state data architecture assessments
  • Target-state architecture design
  • Data modelling
  • Data platform architecture
  • Integration architecture
  • Cloud, on-premises and hybrid architecture
  • Data governance frameworks
  • Master and reference data planning
  • Metadata and data-catalogue strategy
  • Security and access-design considerations
  • Architecture roadmaps
  • Technology evaluation

The value to you

  • One agreed blueprint for how data is stored, integrated and used
  • Less duplication and fewer conflicting versions of the same information
  • Security and access considered by design rather than retrofitted
  • Technology choices made against clear, documented criteria

Typical deliverables

  • Current-state assessment report
  • Target-state architecture and design principles
  • Conceptual, logical and dimensional data models
  • Governance and ownership framework
  • Technology evaluation and architecture roadmap

Situations where this helps

  • Designing a data platform before a major system replacement
  • Establishing data ownership and definitions across departments
  • Evaluating platform options against cost, security and skills requirements

Business intelligence and reporting

Can our leaders see what they need, when they need it?

Build reporting that decision-makers trust and use: clear dashboards, consistent measures and a single view of business information.

Improve your reporting

The business problem

When reports disagree, people stop trusting them. Dashboards built in isolation drift apart, manual reporting consumes skilled time, and slow or cluttered reports discourage use. The result is decisions made on partial or outdated information.

How we approach it

  1. 01We design reporting around the people who use it, their questions and how often they need answers.
  2. 02We build shared semantic models, so every report uses the same definitions and calculations.
  3. 03We test for accuracy and performance, then support adoption with training and clear reporting governance.

What we deliver

  • Executive dashboards
  • Operational dashboards
  • Management reporting
  • Financial reporting
  • Self-service BI
  • KPI scorecards
  • Automated reporting
  • Data visualisation
  • Semantic models and reporting datasets
  • Dashboard optimisation
  • Reporting governance
  • Power BI solutions

The value to you

  • A trusted, consistent view of performance across the organisation
  • Less time spent compiling reports and more time acting on them
  • Faster, clearer dashboards that people return to
  • Controlled self-service, so teams can explore data without creating confusion

Typical deliverables

  • Reporting requirements and wireframes
  • Semantic model and certified reporting datasets
  • Executive and operational dashboards
  • Automated report distribution
  • Reporting governance guide and user training

Situations where this helps

  • Replacing a monthly spreadsheet pack with an automated management dashboard
  • Consolidating several conflicting reports into one certified source
  • Improving the speed and usability of existing Power BI reports

Cloud, on-premises or hybrid?

Where your data platform runs is a business decision as much as a technical one. Our advice is vendor-neutral.

Cloud

Data is stored and processed on infrastructure provided by a cloud vendor. Capacity can grow or shrink with demand and there is less hardware to maintain.

Often suits

Growing data volumes, variable workloads and teams wanting less infrastructure to manage.

On-premises

Data stays on servers your organisation owns or controls. You keep direct control of the environment, along with the responsibility for maintaining it.

Often suits

Strict data-residency requirements, existing infrastructure investment or systems that cannot move.

Hybrid

Some data and workloads run in the cloud while others remain on-premises, connected securely so they work as one environment.

Often suits

Phased modernisation, or a mix of sensitive and less-sensitive workloads.

The right choice depends on

Security and data sensitivity, scale and growth, total cost of ownership, compliance and data residency, existing systems and skills and business requirements and timelines.

Start with a conversation about your data.

Many engagements begin with a short assessment of your current data landscape. We will help you identify the most valuable first step.

Request a Data Consultation

What happens next

  1. 01We review your enquiry and reply to arrange a time to talk.
  2. 02We discuss your objectives, systems and constraints.
  3. 03We suggest a sensible next step, such as a short assessment or a scoped proposal.