Data, Analytics & AI
Data Analytics & AI Consulting Services
Turn disconnected business data into decisions your team can act on. Macrofix helps you plan and build dashboards, data pipelines, analytics automation and practical AI solutions, with clear measures of success, controlled access and a sustainable support plan.
PLAN YOUR DATA PROJECT
Start With the Decision, Not Just the Dashboard
A sales report is only useful when teams agree what counts as revenue. A forecast needs reliable history. An AI assistant needs access to the right information—and boundaries around what it can do. We begin with the business question, the people using the answer and the systems that hold the evidence.
Macrofix can help bring ERP, CRM, finance and operational data into a consistent reporting model. We assess quality, define ownership and build a practical roadmap, whether you need one executive dashboard, a repeatable data pipeline or a carefully evaluated AI pilot.
Data and Analytics Services From Strategy to Support
Choose a focused assessment, a dashboard implementation or a broader data programme. Each engagement defines the sources, deliverables, acceptance checks and operational responsibilities before development begins.
Business Intelligence Consulting & Dashboard Development
Make performance visible with reports that answer specific business questions. We define KPIs with their owners, design data models and build dashboards for finance, sales, operations and leadership. The work includes refresh requirements, access rules, reconciliation and user acceptance—not just charts.
For example, an order-to-cash dashboard can connect pipeline, confirmed orders, invoicing and collections while keeping each measure clearly defined. We agree how users drill into exceptions and what action follows an alert.
- KPI discovery, definitions and reporting ownership
- Semantic models and dashboard design
- Refresh schedules, permissions and reconciliation
- User acceptance, documentation and rollout
Data Engineering & Cloud Data Platforms
Build a reliable route from source systems to analysis. We scope ingestion, transformations, warehouse or lakehouse design, shared data models and orchestration around your existing architecture. Batch and near-real-time patterns are selected according to the actual decision window and operating cost.
Data quality checks, lineage, access controls and failure recovery are part of the design. A pipeline needs named owners, monitoring and a documented response when a source changes or a load fails.
- Source ingestion and transformation pipelines
- Warehouse, lakehouse and shared-model design
- Data quality, lineage and access controls
- Monitoring, recovery and operational handover
Analytics Automation & Reporting Migration
Replace fragile spreadsheet handoffs with repeatable preparation and reporting workflows. We can help profile sources, standardise transformations, schedule approved processes and document exceptions. Alteryx Designer supports visual data preparation and blending; we assess where it fits your team and where a different approach is more appropriate.
When migrating reporting platforms, we inventory existing reports and dependencies, prioritise business-critical outputs and reconcile the new results against agreed benchmarks before retiring anything.
- Data preparation and repeatable Alteryx workflows
- Report inventory and migration prioritisation
- Scheduled automation with exception handling
- Reconciled outputs and controlled cutover
Analytics Training & Adoption
Help analysts and business users understand the numbers they rely on. We can provide role-based walkthroughs, KPI definitions, dashboard usage guidance and administrator handover. Training uses your actual decisions and workflows, with clear boundaries between self-service analysis and governed reporting.
Managed Analytics & AI Support
Keep reporting and automation useful after launch. A defined support engagement can include failed-refresh investigation, data-quality triage, dashboard changes, pipeline monitoring and AI evaluation reviews. We agree service hours, escalation routes, ownership and change approval in the support scope; response commitments are contractual rather than assumed.
Choose Analytics Tools Around Your Business
Microsoft Power BI supports data modelling, reporting and sharing, with a place in the wider Microsoft Fabric ecosystem. Tableau offers visual analysis through desktop, cloud and server options. The right choice depends on your data estate, audience, deployment needs and licensing.
We also scope Alteryx workflows, Amazon QuickSight dashboards (currently branded Amazon Quick Sight), SAP Analytics Cloud analytics and planning, and Zoho Analytics reporting. Existing licenses and skills are assessed before recommending a change.
- Power BI dashboards, models and Fabric readiness
- Tableau visual analytics and deployment planning
- Alteryx data preparation and workflow automation
- Amazon QuickSight / Quick Sight business intelligence
- SAP Analytics Cloud reporting and planning
- Zoho Analytics dashboards and cross-app reporting
Practical AI With Clear Controls
Start with a bounded use case: searching approved internal knowledge, extracting information from documents, assisting a service team or forecasting a measurable operational outcome. We can scope generative AI, enterprise copilots and machine-learning pilots around the available data and the cost of an incorrect answer.
Our delivery plan defines permitted sources, access controls, evaluation examples, human review and monitoring before wider rollout. The NIST AI Risk Management Framework is a useful voluntary reference for structuring risk discussions; using it is not a certification or a guarantee that a system is risk-free.
- Prioritise a bounded AI use case and business owner
- Define approved data sources and access permissions
- Evaluate quality, failure cases and human review
- Monitor outcomes, usage, cost and model changes
A Data Delivery Roadmap With Measurable Checkpoints
We structure delivery around reviewable evidence. Discovery establishes the decision, users and baseline. Data assessment identifies gaps and ownership. A pilot tests the model, dashboard or workflow on representative inputs. Validation checks accuracy, access and performance before rollout, training and support handover.
Acceptance criteria can include reconciliation tolerance, refresh completion, dashboard usability or AI answer quality on a defined evaluation set. Targets are agreed for your use case, not borrowed from a generic success statistic.
- Discover: define decisions, users and success measures
- Assess: profile data quality, access and dependencies
- Pilot: build a focused model, dashboard or AI workflow
- Validate: test accuracy, permissions and real-world use
- Operate: train owners, monitor and improve
Connect Analytics to Your Enterprise Applications
Connect reporting to the systems where work happens. We map the relevant records, keys, update frequency and permissions across Odoo, SAP, Zoho and Salesforce, along with other approved sources.
For NetSuite, Dynamics 365 or Oracle programmes, analytics requirements should be considered alongside the application roadmap. We confirm connector availability, API limits, licensing and data access before committing to an integration approach.
- Finance and operations reporting from ERP records
- Sales and service insights from CRM data
- Inventory, procurement and fulfilment dashboards
- Approved ecommerce and third-party data connections
- Shared definitions across executive reporting
Frequently Asked Questions (FAQs)
Start with your data sources, reporting audience, deployment requirements, existing licenses and team skills. We can assess Power BI, Tableau, Amazon QuickSight, SAP Analytics Cloud and Zoho Analytics against those needs. Alteryx may complement the reporting layer through data preparation and workflow automation. No single platform is the best fit for every organisation.
Yes, we can scope integration with your existing enterprise applications and approved data sources. We first confirm the relevant records, connector or API availability, permissions, licensing, update frequency and data quality. This assessment determines what can be delivered reliably and whether a warehouse or intermediate data model is needed.
Not always. A focused AI use case may work with a controlled set of documents or an existing application. The more important questions are whether the information is suitable, current and permitted for that use, how access is enforced, and how answers will be evaluated. We assess readiness before choosing an architecture or recommending a wider data-platform project.
We can assess and scope a reporting migration. The work starts with an inventory of reports, formulas, data sources, refresh schedules, users and dependencies. We prioritise essential outputs, rebuild or redesign where needed, and reconcile results before cutover. Features do not always map directly between platforms, so exceptions are identified in the migration plan.
Cost depends on the number and condition of data sources, integration complexity, reporting scope, access requirements, testing and ongoing operation. AI projects also require evaluation and usage-cost planning. After discovery, we define a phased scope with deliverables, assumptions and acceptance criteria. Vendor subscriptions, infrastructure and support are identified separately where applicable.
Yes, ongoing support can be scoped for dashboards, data pipelines, automation and AI solutions. We agree the covered components, monitoring duties, change process, service hours and escalation routes. The support plan may include refresh failures, data-quality issues, dashboard enhancements and evaluation reviews as business needs or source systems change.
Let’s Define Your Next Data & AI Project
Tell us which decisions need better information, where your data lives and what your team wants to improve. We can help shape a focused analytics assessment, dashboard rollout, data-engineering engagement or AI pilot with clear deliverables and practical next steps.