Technology with purpose. Built around your business.
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Sciematics Insights
Data Analytics & Business Intelligence

Less time finding numbers.
More time understanding them.

Bring scattered business data into a clearer picture, with consistent measures, useful dashboards and reporting built around the decisions you make.

Illustrative scene of a diverse technology team reviewing a laptop together
The business case

Start with a useful outcome.

A dashboard should answer a question. If it only adds another screen to check, it has missed the point. We start with the decisions your team needs to make, agree what each measure means and examine the source data. The reporting then has a defined owner, a clear refresh cycle and enough context for people to use it responsibly.

Discuss your requirement
Capabilities

What we can help you build.

The scope is shaped around your systems, your information and the work you need to do.

01

Data Analysis

Examine business records to understand patterns, exceptions and the questions that need further investigation.

02

Business Intelligence Dashboards

Create focused reporting views for operational and leadership teams, with suitable access and refresh requirements.

03

Data Visualization

Choose charts and layouts that communicate comparisons, movement and uncertainty clearly.

04

KPI Reporting

Agree metric definitions, sources, owners and reporting frequency so the same number means the same thing across teams.

05

Predictive Analytics

Use historical information to explore future outcomes, with clear assumptions and performance checks.

06

Decision Intelligence

Connect analysis to a decision process, including the action to take, the evidence needed and the person accountable.

Practical applications

Where this can help.

Examples of suitable use cases, to help you think through your own requirements and decide whether there is a worthwhile starting point.

Operational reporting

Replace repeated spreadsheet assembly with a consistent view of current activity.

Leadership visibility

Bring important business measures together with the context needed to interpret them.

Data quality improvement

Trace conflicting reports to their source and establish shared definitions.

A clear working agreement

Know what you are
working towards.

Deliverables are agreed before work begins. A typical engagement may include the following, adjusted to the scope and complexity of your project:

  • A reporting brief and agreed metric dictionary
  • Data preparation and transformation documentation
  • Dashboards or reports with access and refresh settings
  • A handover covering interpretation and maintenance
Before we begin

A useful first conversation.

Bring the reports you already use, the questions they leave unanswered and an overview of the source systems. A small sample of data helps identify quality and integration issues early.

Talk through your idea
Common questions about getting started

What to expect before and during a project.

Yes. Spreadsheets can be a useful starting point when their structure and quality are understood. We also assess whether a more dependable source or reporting process is needed.

Refresh frequency depends on the source systems and the decision being supported. Many business questions are better served by a dependable daily or scheduled refresh than continuous updates.

Access can be designed around roles and the capabilities of the selected platform. Sensitive measures and underlying data need to be considered together.

Connected expertise

Bring the pieces together.

Machine learning

Use your historical data to build models for prediction, classification and recommendations, with evaluation that reflects how the model will be used.

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Start a conversation

What would you like to build?

Tell us what is slowing you down, or what you want to do next. A short description of your business question is all it takes to begin.

Discuss your project