Business Intelligence & Power BI
Turn your data into actionable business intelligence — from interactive dashboards and real-time reporting to data warehousing, ETL pipelines, and predictive analytics. We build Power BI, Tableau, and custom analytics solutions that help Saudi businesses make data-driven decisions.
Book a Free ConsultationWhat is business intelligence, and what does a BI project include?
Business intelligence (BI) turns data from your operational systems into dashboards and reports people can act on, built on a warehouse that pulls cleanly from sources such as Odoo, Dynamics 365 and bank exports. Mantiqi builds BI for Saudi companies on Power BI or Tableau, with a modelled data layer, row-level security and Arabic and English reports, and adds forecasting once there is enough clean history.
Typical timeline: KPI workshop in weeks 1–2, warehouse and ETL in weeks 3–7, dashboards in weeks 6–10.
Why this matters
Most Saudi businesses have data scattered across Odoo, Dynamics 365, banking exports, Excel sheets, and a handful of SaaS tools nobody can connect. Leadership asks for a number; finance produces it three days later via copy-paste from five sources, and by next quarter it's stale. The fix isn't "buy Power BI" (you probably already have it) — it's a deliberate data foundation: a warehouse that pulls cleanly from your source systems, dimensions modeled to your business, and dashboards that load fast enough that people actually use them. Mantiqi builds the analytics layer Saudi enterprises need to stop running their business on lagging Excel screenshots.
What We Deliver
How we deliver
- 01
Data + KPI workshop
Weeks 1–2Two half-day sessions with finance, operations, and leadership to nail down the 10–20 KPIs that actually drive decisions, where each one's source data lives, and what the current pain is in producing them. You leave with a written KPI catalog and source-system map.
- KPI catalog with definitions + owners
- Source-system inventory + data quality notes
- Dashboard wireframes per audience
- Phased delivery roadmap
- 02
Warehouse + ETL build
Weeks 3–7We stand up the data warehouse (Azure Synapse / Snowflake / BigQuery, depending on your cloud), build ETL / ELT pipelines from each source system (Odoo, D365, banking, SaaS APIs), and model the data in a star schema your analysts can actually query.
- Cloud data warehouse
- ETL / ELT pipelines per source
- Star-schema dimensional model
- Data quality + freshness monitoring
- 03
Dashboards + self-service
Weeks 6–10Power BI / Tableau dashboards built per audience (executive, departmental, operational). Self-service layer for power users who want to build their own — with row-level security so people see only what they should.
- Executive + departmental dashboards
- Self-service semantic model
- Row-level security configuration
- Train-the-trainer for analyst team
- 04
Predictive + ongoing
OngoingOnce the foundation is solid, we layer predictive analytics where it adds value — demand forecasting, churn prediction, anomaly detection, customer lifetime value. Quarterly KPI reviews to retire dashboards nobody uses.
- Predictive models in production
- Quarterly KPI / dashboard reviews
- Data-quality scorecard
- Optional managed-analytics tier
Frequently asked questions
Licenses aren't the problem — the data foundation underneath is. Most Power BI deployments connect directly to source databases, which means slow dashboards, brittle queries that break when source systems change, and no row-level security worth the name. We build the warehouse + semantic layer underneath so Power BI becomes the thin presentation layer it's meant to be.
For most Saudi mid-market businesses we recommend Power BI — better Microsoft ecosystem integration, lower license cost, easier hiring market locally, and the gap with Tableau on visualization quality has closed. Tableau where your existing team is deep on it, or for very specific visualization needs Power BI struggles with. We've shipped both extensively.
Default: Microsoft Fabric / Azure Synapse if you're on Azure (which most Saudi enterprises are), Snowflake if you're cloud-agnostic and need the best query performance, BigQuery if you're on GCP. For smaller datasets (under ~500GB total), we sometimes skip the warehouse entirely and use Postgres + dbt — less impressive on the slide deck, dramatically cheaper, and fast enough.
Yes. We've built pipelines from Odoo (PostgreSQL replication or REST API), Dynamics 365 (Dataverse + Synapse Link), Saudi bank statement formats (MT940, CAMT.053, custom CSV from local banks), Salesforce, HubSpot, and most Saudi SaaS tools. New source systems are typically 1–3 days to connect.
Almost never on day one. The first 80% of the engagement is making the data trustworthy and queryable. Once you've got 6+ months of clean historical data flowing into the warehouse, predictive models (forecasting, churn, anomaly detection) become straightforward — typically 2–4 week build per model. Anyone who pitches predictive analytics before the foundation is built is selling you a demo, not a system.
Still have questions?
Our team is ready to help. Reach out and we'll get back to you as soon as possible.
Free offer
Free analytics readiness scorecard
Tell us what your team currently does to produce monthly / quarterly reports. We'll send back a scorecard rating your data foundation across 6 dimensions (source coverage, freshness, modeling, self-service, governance, observability) with concrete recommendations per dimension.
Get the scorecard