Can you build dashboards from Excel or Google Sheets?

Yes when the source structure, identifiers and ownership can support repeatable reporting. Data cleaning or redesign may be needed before a dashboard is dependable.

Can DATA OVEN analyse the data before building the dashboard?

Yes. Data analysis can be a separate or earlier step to understand quality, trends, exceptions and KPI definitions before investing in the visual reporting layer.

Can you improve an existing report?

Yes. We review the source data, metric definitions, calculations, refresh process, users and the decisions the report is expected to support.

Business service

Make business data easier to trust, explain and use for recurring decisions.

Turn operational data into clear reporting with agreed KPI definitions, repeatable preparation, decision-focused dashboards, refresh ownership and documented limitations.

When this fits

Dashboards, Data Analytics and Reporting Services

This service is structured around the business process first, then the technology required to support it.

Swipe through common use cases

Leadership receives reports too late or in inconsistent formats

Different teams use different definitions for the same KPI

Important exceptions and trends are hidden inside spreadsheets or exports

The business needs analysis, Power BI or Looker Studio but the source data and ownership need structure first

Swipe through expected outcomes

Agreed KPI and metric definitions

A traceable source-to-report model

Decision-focused dashboards and analysis

Clear refresh, access and maintenance ownership

Analytics visual

Move from raw source data to a decision with definitions in the middle.

Dashboards become more useful when data preparation, KPI definitions and validation are treated as part of the reporting system.

Operating flow

Swipe on mobile to follow the sequence.

01Source data
02Clean and define
03Analyse
04Dashboard
05Decision

Illustrative process only. The exact sequence, validation and ownership depend on the approved business workflow.

Reporting demo

Operations performance

Last 30 daysAll regions

Orders completed

1,284

+8.4%

On-time rate

94.2%

+2.1%

Exceptions open

-6

Weekly completion index

Exceptions needing action

Delayed approval8

Missing source record5

Integration retry4

Fictional demonstration dashboard. It is not a screenshot of a client environment and does not use client data.

Delivery structure

From scattered data to dependable recurring reporting.

The exact sequence depends on the approved scope, systems and risks, but each workstream has a clear purpose.

Swipe through the workstreams

Business questions and metrics

Agree what users need to understand, which records count and how each important KPI is defined.

Data preparation

Clean, map and structure approved source data so the reporting method can be repeated.

Analysis and dashboard design

Create the required analysis, KPI views, trends, comparisons and exceptions for the intended audience.

Validation and reporting operations

Reconcile important outputs and document refresh, sharing, maintenance and issue ownership.

What you receive

Reporting assets your team can refresh, explain and use.

Deliverables are defined around the agreed workflow so both business owners and technical maintainers can understand what was delivered.

Swipe through deliverables

Metric dictionary

Definitions, calculation notes and ownership for the measures that matter to the report.

Source and transformation map

A record of where reporting data comes from and how it is cleaned or prepared.

Data analysis

Repeatable analysis of agreed trends, exceptions, comparisons or operational questions.

Power BI or Looker Studio dashboard

Decision-focused reporting in the platform that best fits sources, users, licensing and governance.

Validation record

Checks that important totals and example records align with approved source evidence.

Refresh and handover notes

Access, refresh, distribution, maintenance and known limitation documentation.

Technology approach

Power BI, Looker Studio, Excel, Google Sheets, SQL, Python and approved connectors can be used according to the source data, analytical complexity, audience and long-term ownership. A dashboard platform is selected after the reporting problem is understood.

Scope clarity

Important boundaries.

A dashboard cannot make unreliable source data trustworthy without addressing the underlying data problem

Licensing, connector availability and tenant configuration remain platform dependencies

Analysis and reporting support decisions but do not guarantee a particular business outcome

Questions

What teams usually ask before starting.

Power BI is often a strong fit for Microsoft environments and richer data modeling. Looker Studio is often convenient for Google-centered reporting. The right choice depends on sources, users, licensing, sharing and maintenance needs.

Related services