# All your data. One source of truth.

> Your numbers live in a dozen tools and never agree. We consolidate them into a governed cloud data warehouse: clean, historical, and ready for reporting, BI, and AI. Complete data warehousing setup for companies in the USA, UK, and India.

**Service:** Data Warehousing  
**Provider:** Parix Digital Pvt. Ltd.  
**Regions served:** United States, United Kingdom, India  
**URL:** https://www.parix.digital/services/data-warehousing  
**Contact:** sales@parix.digital · +91 91068 33831

## Key takeaways
- Parix Digital builds modern cloud data warehouses (Snowflake, BigQuery, Redshift) that unify every tool into one governed source of truth.
- Includes reliable ETL/ELT pipelines, dbt data modeling, governance, and a BI semantic layer.
- Delivers trustworthy, AI-ready data with full history. No more conflicting reports or manual CSV exports.

## The reality: You have plenty of data. You just can't trust it.
- **Data Silos Everywhere** — Sales in the CRM, finance in accounting, ops in spreadsheets. No one can answer a cross-team question without a week of exports.
- **Reports Take Days** — Analysts spend more time gathering and cleaning data than analysing it.
- **Conflicting Numbers** — Two reports, two different revenue figures, and an hour-long meeting about whose spreadsheet is right.
- **No History** — Systems overwrite data, so you can't see trends, compare periods, or audit what changed and when.
- **Manual CSV Gymnastics** — Critical dashboards depend on someone exporting CSVs every Monday. It breaks the moment they're on leave.
- **Can't Support AI/ML** — Messy, scattered data means any AI or forecasting project stalls before it starts.

## What we deliver: A governed warehouse your whole company trusts
### Data Audit & Architecture
We catalogue every source and design the right warehouse architecture.

- Source System Inventory
- Warehouse Selection
- Cost & Scale Planning
- Reference Architecture

### ETL/ELT Pipelines
Automated, monitored pipelines that ingest data from every tool reliably.

- Connectors (Fivetran/Custom)
- Incremental Loads
- Schema Drift Handling
- Retry & Alerting

### Data Modeling
Clean, documented models built on star schema and dbt.

- Star/Dimensional Models
- dbt Transformations
- Version-controlled Logic
- Reusable Metrics

### Governance & Quality
Tests, access control, and lineage.

- Automated Data Tests
- Role-based Access
- Column-level Lineage
- PII Handling & Masking

### BI & Semantic Layer
A consistent metrics layer for every BI tool.

- Semantic Metric Layer
- Power BI/Looker/Metabase
- Self-serve Datasets
- Curated Dashboards

### Orchestration & Monitoring
Scheduled, observable pipelines.

- Airflow/Dagster
- Freshness & SLA Checks
- Failure Alerting
- Cost Monitoring

## Process
1. **Assess** — Inventory sources, define metrics, choose the architecture.
2. **Model** — Design clean, documented data models.
3. **Pipeline** — Build automated ELT pipelines and load history.
4. **Operationalise** — BI layer live, tests and monitoring in place, team trained.

## Why Parix Digital
Data infrastructure built to be trusted.

- One governed source of truth across all tools
- Reliable, monitored pipelines. No Monday CSV panic
- Full history retained for trends and audits
- Documented models anyone on the team can use
- AI/ML-ready clean data foundation
- Cost-tuned for your data volume

## FAQ
### Which data warehouse should we use?
It depends on your stack, scale, and budget. We are platform-agnostic and recommend Snowflake, BigQuery, or Redshift based on your needs. All three offer US and UK/EU regions, so data can stay resident where your compliance team needs it.

### Can you pull data from all our tools?
Yes. We connect CRMs, ERPs, ad platforms, databases, spreadsheets, and SaaS APIs using managed connectors or custom pipelines, covering the common US SaaS stack (Salesforce, HubSpot, Stripe) and UK favourites (Xero, Sage) alike.

### Will this work with our BI tool?
Yes. We build a clean semantic layer that feeds Power BI, Looker, Metabase, Tableau, or whatever you use.

### How do you ensure the data is accurate?
We add automated data-quality tests, freshness checks, and column-level lineage, plus alerting. PII is masked and access is role-based, aligned with UK GDPR and US privacy laws such as the CCPA.

### Will this prepare us for AI and ML projects?
Absolutely. A clean, governed warehouse is the foundation for any serious analytics or AI work, and it's the first thing we build before data science engagements in the US, UK, or India.