Consolidated reporting for a multi-branch group
A retail or hospitality group whose branches run on different systems needs one daily view of sales, inventory, and margin, without regional teams compiling spreadsheets by hand.
GIntelligence & Data
Data Engineering & BINumbers your leadership can stop debating.
AMA GROUP designs the pipelines, warehouses, and reporting layers that consolidate data from your operational systems into trusted, timely, clearly defined metrics.
- Code
- G
- Practice
- Intelligence & Data
- Scope areas
- 8
- Delivery phases
- 6
Overview
Reliable pipelines, governed warehouses, and executive dashboards that turn scattered data into decisions.
Data engineering is the foundation that makes analytics trustworthy. It covers ingesting data from ERP, CRM, e-commerce, finance, and operational systems; cleaning and modeling it; storing it in a warehouse or lakehouse; and exposing it through governed semantic models and dashboards. Business intelligence is the layer leadership sees, but its value depends entirely on what sits beneath it.
Many organizations in Saudi Arabia and abroad still run on a patchwork of spreadsheets, manual exports, and system-specific reports, often with the same KPI calculated three different ways. As performance management becomes more data-driven across the private and public sectors, that patchwork turns into a liability: slow month-end closes, conflicting figures in the boardroom, and decisions made on stale information. The PDPL adds another dimension, requiring organizations to know where personal data lives and who can access it.
AMA GROUP starts with decisions, not tools: which questions leadership needs answered, how often, and at what level of detail. From there we design a layered architecture of ingestion, tested transformation models, a governed semantic layer, and bilingual Arabic and English dashboards, and we document every metric definition so finance, operations, and executives read the same number the same way. We favor proven, maintainable stacks your team can own after handover.
Scope of work
What this service can cover. Most engagements combine several of these areas.
Data pipelines
Batch and near-real-time ingestion from databases, APIs, files, and SaaS platforms using ELT patterns, with orchestration, retries, and data quality checks at every stage.
Data warehouses
Dimensional and lakehouse models on platforms such as Snowflake, BigQuery, Microsoft Fabric, or PostgreSQL, designed around how your organization actually reports.
Power BI
Semantic models, DAX measures, row-level security, incremental refresh, and deployment pipelines, built for performance and governed reuse across reports.
Executive reporting
KPI frameworks and leadership dashboards with clear definitions, targets, and drill-down paths, distributed on schedule in Arabic and English.
Database architecture
Schema design, indexing, partitioning, and replication for transactional and analytical workloads, including separating reporting load from operational databases.
Forecasting
Statistical and machine-learning forecasts for demand, revenue, cash flow, or capacity, with transparent assumptions and ongoing accuracy tracking against actuals.
Data visualization
Purpose-built visuals with charts chosen for the question, accessible color, and RTL-aware layouts, whether in BI tools or custom web dashboards.
Analytics
Cohort, funnel, segmentation, and operational analyses that answer specific business questions and are built to be rerun, not rebuilt every quarter.
Typical use cases
Representative scenarios where organizations need this service: examples of the need, not past client engagements.
A faster finance month-end
A finance team automates feeds from the ERP and bank statements into a warehouse, so reconciliations and management accounts rely on pipelines instead of manual copy-and-paste.
Demand forecasting for retail and distribution
A distributor forecasts demand by product and region, accounting for seasons such as Ramadan and back-to-school, to inform purchasing and help reduce both stock-outs and overstock.
Operational visibility in logistics
A logistics operator tracks shipment status, SLA adherence, and fleet utilization in near real time, with alerts when performance drifts from target.
Bringing order to a sprawling Power BI estate
An organization with hundreds of ungoverned reports consolidates them onto shared semantic models with consistent measures, row-level security, and acceptable load times.
Strategic KPI tracking in the public sector
A government entity tracks performance indicators against its strategic objectives in bilingual dashboards, with clear lineage from each figure back to its source system.
Delivery approach
Clear phases with defined outputs, so you can follow progress and make decisions at every stage.
- Step 1
Decision and metric discovery
We interview stakeholders to list the decisions, KPIs, and definitions that matter, and inventory every source system involved.
- Step 2
Data audit and architecture
We profile source data quality, select the platform, and define raw, staged, modeled, and serving layers with clear ownership for each.
- Step 3
Pipeline and model build
We implement ingestion and version-controlled dbt transformations, with automated tests and documentation generated directly from the code.
- Step 4
Semantic layer and dashboards
We build measures and row-level security, then iterate on dashboards in short review cycles with the people who will actually use them.
- Step 5
Validation and reconciliation
Every key figure is reconciled against source systems and finance-approved numbers before sign-off, and discrepancies are traced to their root cause.
- Step 6
Operate and hand over
We set up freshness and failure alerts, write runbooks, and train analysts so your team can extend the platform independently.
Technical capabilities
Tools and platforms we select from, based on your context, constraints and existing stack.
Ingestion & orchestration
- Apache Airflow
- Dagster
- Airbyte
- Fivetran
- Azure Data Factory
- Apache Kafka
- Debezium
Warehousing & storage
- Snowflake
- Google BigQuery
- Microsoft Fabric
- Amazon Redshift
- Databricks
- PostgreSQL
- ClickHouse
Transformation & quality
- dbt
- SQL
- Python
- Apache Spark
- Great Expectations
- Soda
BI & visualization
- Power BI
- DAX
- Tableau
- Apache Superset
- Metabase
- Apache ECharts
- D3.js
Forecasting & analysis
- pandas
- scikit-learn
- Prophet
- statsmodels
- Jupyter
- MLflow
Technologies listed are capabilities and ecosystems we work with, not partnerships, certifications or endorsements.
Deliverables
What you receive during and at the end of the engagement. The exact set depends on the agreed scope.
- Source system inventory and data quality assessment
- Target data architecture and platform recommendation
- Production pipelines with orchestration, monitoring, and alerting
- Documented data models and a searchable data dictionary
- KPI catalog with business-approved definitions and named owners
- Power BI semantic models and dashboards with row-level security
- Forecasting models with accuracy reports against actuals
- Runbooks and hands-on training for your analysts
Direct connections can work for a single source with modest volumes. A warehouse becomes worthwhile when you combine several sources, need history that operational systems do not keep, want one set of metric definitions across reports, or need to protect production databases from reporting load. We assess this early so you neither over-build nor under-build.
Related industries
Sectors where this service is commonly needed.
Financial Services & Fintech
Secure digital banking, payments and analytics platforms engineered for trust and scale.
Retail & E-commerce
Unified commerce platforms that connect online stores, apps, branches and fulfillment in one experience.
Logistics & Supply Chain
Fleet, warehouse and delivery platforms that give real-time visibility from first mile to last.
Government & Public Sector
Citizen-centered digital services, interoperable platforms and Arabic-first experiences for public entities.
Energy & Utilities
Asset monitoring, field operations and analytics platforms for energy, utilities and sustainability.
Related concept projects
Design explorations showing how this service could come together in a real product, not delivered client work.
Concept Project: A design concept that shows how we think, not a delivered client project.Manufacturing & Industrial Operations
Mizan: A Unified Enterprise Resource Platform
An Arabic-first ERP exploration that brings finance, procurement, inventory and production planning onto one operational record for a multi-site manufacturer.
View conceptConcept Project: A design concept that shows how we think, not a delivered client project.Internal Operations in Financial Services
Sanad: An Arabic-First Enterprise Assistant
An AI assistant concept that answers a financial institution’s staff from its own policies and procedures, citing its sources and respecting permissions.
View conceptConcept Project: A design concept that shows how we think, not a delivered client project.Retail & E-commerce
Rawaj: A Unified Commerce Ecosystem
A headless commerce exploration that connects web store, mobile app, physical branches and marketplaces through one inventory and a seamless Arabic shopping experience.
View conceptIllustrative Solution: A model of a possible solution, not completed client work.Finance & Performance Management
Marsad: A Financial Analytics Workspace
An illustrative analytics platform that gives the finance office one trusted number, from the executive dashboard down to the original journal line.
View conceptConcept Project: A design concept that shows how we think, not a delivered client project.Transport & Logistics
Masar: Fleet & Last-Mile Orchestration
A logistics platform concept that connects planning, dispatch, drivers and customers in one live picture, from the warehouse to the recipient’s door.
View conceptRelated services
Services that often work alongside this one.
AI & Intelligent Systems
LLMs, agents, RAG and computer vision grounded in your data, with clear controls on quality, security and cost.
Enterprise Software
ERP, CRM, HR and finance systems shaped around how you work: integrated, adaptable and built to grow with you.
Cloud & DevOps
Secure, scalable cloud foundations, automated delivery pipelines and full observability on AWS, Azure and Google Cloud.
API & Integration
REST and GraphQL APIs, payments, webhooks, and event-driven integrations that make separate systems work as one.
Tell us what you are building.
Share your goals for Data Engineering & BI. We will come back with a clear approach, a proposed team shape and practical next steps.