Data Analytics & BI Dashboards
That Drive Real Decisions
We build the data infrastructure and analytics layer that turns raw events into dashboards, forecasts, and decisions your teams actually trust.
What we build
End-to-end data & analytics services
From raw pipeline plumbing to predictive models — every layer of the modern analytics stack covered under one engagement.
Data Warehousing
Modern cloud data warehouses on Snowflake, BigQuery, or Redshift — schema-designed for query performance, cost efficiency, and the analytical workloads your teams run every day.
Data Pipelines & ETL/ELT
Automated ingestion, transformation, and loading pipelines that move data from every source — databases, SaaS tools, event streams, and flat files — into your warehouse reliably and on schedule.
Data Modelling with dbt
Version-controlled, tested, and documented data models built with dbt — so your metrics are defined once, trusted everywhere, and any analyst can trace a number back to its source.
BI Dashboards & Reporting
Self-serve dashboards in Looker, Metabase, Power BI, or Superset — designed around how your teams actually think, not what the tool defaults to. Beautiful, fast, and actionable.
Real-Time Event Streaming
Kafka, Kinesis, and Flink-powered streaming pipelines for product analytics, fraud detection, operational monitoring, and any use case where waiting for a batch job is too slow.
Predictive Analytics & ML
Churn prediction, demand forecasting, customer LTV, and anomaly detection — predictive models trained on your warehouse data and surfaced where decisions are actually made.
Data Observability
Automated data quality tests, freshness monitoring, schema change alerts, and lineage tracking — so data issues are caught before a stakeholder finds a wrong number in a dashboard.
Metrics Layer & Semantic Layer
A single source of truth for your business metrics — defined, versioned, and accessible to every BI tool, notebook, and AI query so everyone calculates revenue the same way.
Analytics Engineering
Ongoing model maintenance, dashboard iteration, pipeline optimisation, and stakeholder enablement — embedded analytics engineers who make your data platform better every sprint.
The modern data stack
Every layer of your analytics platform
We select, build, and connect the right tools at every layer — no vendor lock-in, no over-engineering.
The modern data stack
Every layer of your analytics platform
We select, build, and connect the right tools at every layer — no vendor lock-in, no over-engineering.
Collect From Every Source
Databases, SaaS tools, and event streams — ingested reliably and on schedule with no custom ETL code.
- Managed connectors eliminate custom ETL code and ongoing maintenance overhead
- Schema change detection prevents silent failures from breaking downstream dashboards
- Supports both real-time event streams and nightly batch loads from the same pipeline
Warehouse Built for Scale
Store petabytes of structured and semi-structured data in a cloud warehouse optimised for analytical workloads.
- Schema designed for analytical workloads — fast query performance at any data volume
- Automatic scaling means storage and compute grow without manual intervention
- Cost-optimised partitioning and clustering reduce query spend as data accumulates
Metrics Defined Once, Trusted Everywhere
Model, test, and document your data so every number traces back to its raw source in seconds.
- dbt models are version-controlled so metric changes are reviewed like application code
- Automated tests catch bad data before it reaches stakeholder dashboards
- Full data lineage lets any analyst trace a number back to its raw source in seconds
Insights in the Tools Teams Already Use
Self-serve dashboards, notebooks, and AI queries — surfaced where your teams already work every day.
- Self-serve dashboards reduce analyst bottlenecks and data team backlog significantly
- Semantic layer ensures every tool calculates revenue, conversion, and churn identically
- Embedded ML models surface predictions and anomalies directly inside existing reports
Where data drives value
Analytics built for every team, not just data teams
We design dashboards and data models around how each function thinks — not generic out-of-the-box templates.
Finance
Real-time P&L, revenue forecasting, budget variance, and automated close-process reporting that replaces manual spreadsheets.
Product
Funnel analysis, feature adoption, retention cohorts, and activation dashboards built around your north star metric.
Operations
Supply chain visibility, SLA monitoring, capacity planning, and exception alerting across your operational systems.
Marketing
Campaign attribution, customer acquisition cost, LTV:CAC ratio, and channel performance dashboards that match how you think.
Sales
Pipeline velocity, win-rate by segment, rep performance, and forecast accuracy — synced live from your CRM.
Risk & Compliance
Transaction monitoring, anomaly detection, audit-ready data lineage, and automated regulatory reporting.
5B+
Data points processed
3×
Faster insight delivery
95%
Forecast accuracy
Real-time
Dashboard refresh rate
Our approach
How we build your data platform
Metric-first, not tool-first — we start with what decisions need to be made, then build backwards.
Data Mapping
Inventory every data source, define your core metrics, and identify the gaps between what you have and what you need.
Stack Design
Pipeline Build
Dashboards
Forecast & Grow
What you gain
From raw data to decisions your teams trust
Faster Decisions
Dashboards your teams check every morning — not reports that land in inboxes after a 48-hour delay.
Data You Can Trust
Automated quality tests and observability alerts catch bad data before it reaches a stakeholder.
No More Manual Reports
Automated pipelines replace spreadsheet exports — analysts spend time on insight, not data prep.
Predict, Don't React
Forecasting and anomaly detection that flags problems before they show up in monthly results.
Self-Serve Analytics
Business users find their own answers — reducing analyst bottlenecks and data team backlog.
One Source of Truth
A semantic layer where every team calculates revenue, conversion, and churn the same way.
Our team
What Makes mabzone Your Go-To Data Analytics Partner
Data engineers, analytics engineers, and BI specialists who care as much about decision quality as pipeline uptime.
Why mabzone
Why businesses choose mabzone for data analytics
The data engineering standards that make our platforms trusted, fast, and built to last.
End-to-end data stack
Ingestion, transformation, storage, and visualisation delivered as a single coherent system.
Real-time & batch
Streaming pipelines for operational decisions and batch processing for deep analysis — both, together.
AI/ML integration
Predictive models and anomaly detection embedded directly into your dashboards and data products.
Data governance built in
Column-level access control, data lineage tracking, and PII masking from the first pipeline.
Warehouse-agnostic
We work with Snowflake, BigQuery, Redshift, and open-source stacks — whatever fits your cost model.
Start with a free data audit
Share your requirements — we'll map your sources, identify gaps, and get you a delivery plan within 48 hours.
Technologies
Our data & analytics stack
Snowflake
Warehouse
BigQuery
Warehouse
Redshift
Warehouse
dbt
Transform
Airflow
Orchestrate
Fivetran
Ingestion
Kafka
Streaming
Looker
BI
Power BI
BI
Python
Language
Apache Spark
Processing
Compliance & Standards
Compliance Standards That Shape Our Data Analytics Practice
We build data platforms that meet global privacy, security, and governance requirements — so your analytics are trusted, auditable, and defensible.
GDPR (EU)
Lawful data collection, storage, and processing for EU residents
CCPA
Consumer data rights and opt-out controls for California users
HIPAA
Protected health information in clinical and health analytics
SOC 2 Type II
Security and availability controls for data platforms
ISO 27001
Information security management for data infrastructure
PCI DSS
Secure handling of payment data in analytics pipelines
NIST Privacy
Privacy framework for responsible data management practices
PIPEDA (Canada)
Canadian privacy law for personal data collection and use
DPDP Act (India)
India's Digital Personal Data Protection Act compliance
ISO 8000
Data quality management and master data standards
Data Analytics FAQs
Common questions about data analytics and business intelligence.
Let's Build Together
Ready to trust your data?
Start with a free data audit — we'll map your sources, identify gaps, and show you exactly what's possible with the data you already have.