Skip to main content
Data & Analytics

Business intelligence

BI that boards actually use

Request BI advisory
The Engagement

Business intelligence

Three situations signal that BI advisory is overdue. Each one costs the organization time and credibility at the board level.

Talk to an advisor
Methodology

Our Approach

A four-phase advisory rhythm, assess, design, advise, support, repeated across every engagement.

  1. Requirements mapping

    Interviews with the CEO, CFO, COO, and the heads of each business unit to identify the fifteen to twenty decisions they make on a recurring basis and the data each decision requires. The output is a decision register, not a feature list. The register determines what the BI architecture must deliver.

  2. Data architecture and model design

    Assessment of existing data sources: ERP, CRM, HRIS, financial systems, operational databases. Design of the data model that connects these sources to the KPIs in the decision register. Identification of gaps: data that should exist but does not, data that exists but is ungoverned, data that is governed but inaccessible to the BI platform. Platform recommendation follows the architecture, not the other way around.

  3. KPI framework and reporting design

    Definition of each KPI: the formula, the data source, the refresh cadence, the owner, and the threshold that triggers an alert or escalation. Dashboard wireframes for each audience (board, C-suite, department heads, operational teams). Review cycles with the stakeholders who will use the output, not just the team that builds it.

  4. Validation and handoff

    Parallel run of the new reporting layer against the legacy process for one to two reporting cycles. Discrepancies are traced to root cause and resolved. User acceptance with the actual decision-makers who will open the dashboards on Monday morning. Documentation of the data model, KPI definitions, and platform configuration so the internal team or vendor can maintain the system without the consultant.

Strategic Outcomes

What success looks like

A decision register that maps each recurring executive and operational decision to the data it requires, the KPI that measures it, and the cadence at which it must be refreshed.
A data architecture document that specifies how existing systems (ERP, CRM, HRIS, financial platforms) feed the BI layer, with every gap identified and remediation scoped.
KPI definitions that include formula, data source, owner, refresh cadence, and escalation threshold. No ambiguity about where a number comes from.
Dashboard wireframes reviewed and accepted by the executives who will use them, not by the IT team alone.
Platform recommendation (Power BI, Tableau, or alternative) grounded in the architecture requirements, not in vendor preference.
Handoff documentation sufficient for the internal team or systems integrator to build, deploy, and maintain the solution.
A decision register that maps each recurring executive and operational decision to the data it requires, the KPI that measures it, and the cadence at which it must be refreshed.
A data architecture document that specifies how existing systems (ERP, CRM, HRIS, financial platforms) feed the BI layer, with every gap identified and remediation scoped.
KPI definitions that include formula, data source, owner, refresh cadence, and escalation threshold. No ambiguity about where a number comes from.
Dashboard wireframes reviewed and accepted by the executives who will use them, not by the IT team alone.
Platform recommendation (Power BI, Tableau, or alternative) grounded in the architecture requirements, not in vendor preference.
Handoff documentation sufficient for the internal team or systems integrator to build, deploy, and maintain the solution.
Who This Is For

Built for these teams

CEOs and board members who receive quarterly reports built on inconsistent data and want a single version of the truth they can interrogate in real time.
CFOs who need financial KPIs calculated from governed sources, refreshed on a cadence that matches decision cycles, and defensible under audit.
CIOs and IT directors evaluating Power BI, Tableau, or other platforms and needing an architecture-first recommendation that accounts for existing systems and data quality.
COOs and operations directors managing multi-site or multi-entity operations where performance data must be comparable across units.
Compliance and governance teams at entities reporting to the Central Bank of the UAE (CBUAE) or other regulators that require documented, auditable KPI methodologies.
CEOs and board members who receive quarterly reports built on inconsistent data and want a single version of the truth they can interrogate in real time.
CFOs who need financial KPIs calculated from governed sources, refreshed on a cadence that matches decision cycles, and defensible under audit.
CIOs and IT directors evaluating Power BI, Tableau, or other platforms and needing an architecture-first recommendation that accounts for existing systems and data quality.
COOs and operations directors managing multi-site or multi-entity operations where performance data must be comparable across units.
Compliance and governance teams at entities reporting to the Central Bank of the UAE (CBUAE) or other regulators that require documented, auditable KPI methodologies.
Common questions

Frequently asked

Procurement-grade answers to the questions counsel and CIOs ask most.

  • Business intelligence (BI) is the disciplined production of trusted dashboards and reports the operating team uses to run the business day to day; analytics is the broader practice that includes forecasting, segmentation, and modelling. BI answers 'what happened and what is happening,' analytics answers 'why and what will happen next.' For UAE enterprises, BI is the foundation that has to be governed before any analytics initiative produces decisions the board will trust.

  • A data warehouse is the structured store of historical data; BI is what the organization does with it. The warehouse without BI is an expensive archive; BI without a governed warehouse is dashboards built on shifting sand. Bahgat Expert specifies both in the same engagement so the model layer (metrics, dimensions, hierarchies) sits between the warehouse and the dashboard rather than being re-implemented per report.

  • Eight to sixteen weeks for a first executive dashboard set on a single business domain (finance, sales, operations). Discovery and metric definition is two to three weeks; data pipeline and model build is four to eight; dashboard build and validation is three to four. The duration is driven by source-system complexity and data quality, not by the BI tool. Bahgat Expert sequences the work so the first usable dashboard is in front of the executive team by week eight at the latest.

  • The recommendation depends on the organization's existing stack and licensing posture: Microsoft Power BI for organizations already invested in Microsoft 365, Tableau for visualization-heavy use cases, Qlik for enterprises with complex associative analysis needs, and Looker for those built on a modern data warehouse. Bahgat Expert is tool-neutral; the choice follows the metric model and the operating context, not the other way around.

  • Three controls. A documented data lineage from source to dashboard so anyone can trace a number back to its origin. A monitoring layer that flags pipeline failures, freshness lapses, and out-of-range values before the executive team sees them. A formal data ownership model where each KPI has a named owner accountable for its accuracy. Without these the dashboards eventually lose credibility and the executive team stops using them.

Data Engagement

Discuss business intelligence

Discuss governance, dashboards, and analytics frameworks built for the boardroom rather than the data team.

Chat with UsView Case Studies

Request a Consultation

Start your business intelligence engagement

Two short steps. We respond within two business days.

Step 1 of 2