Discuss your project
Business Systems & ERP

Data analytics and business intelligence

Most organisations hold the data they need, but it sits in separate systems, disagrees between reports and takes days to assemble. We define each measure, bring data into a governed warehouse and build trusted dashboards.

Discuss your project How the work is delivered

A good fit if

  • Monthly reporting means stitching spreadsheet exports from several systems by hand.
  • Leadership wants dashboards, but departments report different numbers and nobody owns definitions.
  • You license Power BI or another tool, but reports are slow, fragile or unused.
  • You want to move from describing what happened to forecasting what comes next.

What is included

  • Discovery of the decisions, questions and users to serve
  • Metric dictionary: definition, formula, owner and source per measure
  • Source inventory and data quality assessment, with fixes at source
  • Monitored pipelines into a reporting warehouse or lakehouse model
  • Semantic model and dashboards in Power BI or similar
  • Row-level security tested with real roles; refresh monitoring

What this service is

Analytics finds patterns and trends in your ERP, CRM, finance and operational data; business intelligence turns them into reliable dashboards. Both need agreed definitions, a sound data foundation and owners for the numbers, not just new software. See data analytics for businesses.

Better decisions

Market, customer and operational trends clear enough to act on.

Efficiency

Find bottlenecks, delays and waste, and track whether fixes work.

Customer experience

What customers buy, how they behave, where service falls short.

Risk

Overdue receivables, unusual transactions or supply shortfalls, spotted early.

Sector uses and an example definition

Retailers and distributors optimise inventory and reduce waste; financial services detect fraud; healthcare providers plan capacity and resources. More in the data-driven shift in Nigerian industries.

Demonstration, not a client project
FieldEntry
MeasureOn-time delivery rate
DefinitionShare of sales order lines shipped on or before the promised date
FormulaLines shipped on time ÷ lines shipped in the period
SourceERP sales orders and shipments
OwnerOperations manager
ExcludesCancelled lines; orders on customer hold

Start small, then go further

  1. ObjectivesClear goals for one business area.
  2. PilotA first project that demonstrates value.
  3. ToolsFit to needs and budget, security built in from the start.
  4. PredictOn trusted data: forecasting demand, cash flow or churn, and anomaly detection.

Often that is Power BI with a warehouse on Azure, AWS, Google Cloud or Snowflake, or local hosting, chosen for data location and connectivity, since there is no major public cloud region in Nigeria (naming a platform is not a partner claim). Trusted data also powers natural-language questions and assistants answering from your information: AI automation, generative AI, and system integration to keep data flowing.

Delivery

How the work is delivered

  1. Discover

    Agree the decisions and questions to support, the users and the data sources.

    Output: Discovery notes and prioritised questions.

  2. Define

    Write each measure's formula, owner and source; agree governance rules; test data quality.

    Output: Metric dictionary and quality findings.

  3. Build the foundation

    Pipelines and a warehouse model, with refresh schedules, logging and alerts on failed loads.

    Output: Tested pipelines and data model.

  4. Build and validate

    Build dashboards with their users and reconcile figures against trusted reports before release.

    Output: Validated dashboards and reconciliation notes.

  5. Launch and hand over

    Train users, document everything so another analyst can maintain it, and agree who owns changes.

    Output: Live dashboards, documentation, ownership.

Scope at a glance

Not included unless agreed

  • BI, cloud and warehouse licences, bought from the vendor
  • Source-system data fixes or post-handover development, unless agreed
  • Statistical or actuarial advice for regulated decisions

What we need from you

  • A business owner per area to agree definitions and priorities
  • Read access to source systems, or exports where needed
  • Current reports, and your security, data protection and location requirements

Before handover

  • Every measure traces to a written definition and a named owner
  • Figures reconciled with trusted reports, and differences explained
  • Failed refreshes alert a named person instead of going stale silently

What affects the cost

  • Number of data sources and ease of access
  • Source data quality and cleaning needed
  • Areas, measures, dashboards, refresh frequency, volumes
  • Data protection, location; training and user numbers

No package prices: estimates in naira from an agreed scope, taxes shown separately.

Questions buyers usually ask

Do we need a data warehouse, or can Power BI connect directly to our systems?

Direct connections can work for a few sources and modest volumes. Combining systems, keeping history or sharing definitions usually makes a warehouse simpler and faster to maintain. We recommend the lighter option when it is enough.

Which BI tool should we use?

Often the one you already license; Power BI is common with Microsoft 365, and we work with others. The data model and definitions matter more than the tool.

How do you handle personal data in analytics?

We use only the data each report needs, de-identify or aggregate where possible, restrict and log access by role, and keep data where you choose, in a local data centre or a cloud region abroad. The Nigeria Data Protection Act 2023, including its transfer rules, still applies; this is not legal advice.

Spending days assembling reports?

Tell us which reports matter most and where the data lives. We will reply to arrange a conversation about a first project.

Discuss analytics