Data Analytics Services
Turn Raw Data Into Decisions That Drive Growth
We build data pipelines, BI dashboards, and real-time analytics systems that replace guesswork with evidence — so your team makes faster, smarter decisions every day.
Snowflake / BigQuery / Redshift
Power BI & Tableau
Real-time Kafka Streams
GDPR & HIPAA Ready
Data PipelineRunning
Raw Sources
Postgres · Shopify · Salesforce · GA4
Transform & Enrich
dbt models · deduplication · joins
Live Dashboard
Looker · Power BI · Superset
150+
Pipelines
99.9%
Uptime
<5min
Latency
150+
Data Projects Delivered
40%
Avg Decision-making Speed Gain
100+
Data Source Connectors
99.9%
Pipeline Uptime SLA
The Problem
Seven systems. Zero answers.
Before & after: from chaos to single source of truth
The average mid-market company has 7+ tools with data that never talks to each other.
Before: 7 silos
Shopify
Salesforce
Google Analytics
Klaviyo
QuickBooks
Zendesk
Stripe
After: one warehouse
Snowflake Warehouse
Live P&L dashboard
True CAC by channel
Unified customer view
Automated reporting
8 hrs
Lost every week
Average executive time spent reconciling data across siloed tools before every leadership meeting.
+40%
Faster decisions
Average decision-making speed improvement after unifying data into a single analytics layer.
Pipeline Types
The right pipeline for your data
Batch ETL
Scheduled extraction, transformation, and loading
Nightly or hourly pipelines that collect from 100+ sources, apply dbt transformations, and load clean data into your warehouse. Idempotent, testable, and monitored — not fragile cron jobs.
Best for
Dashboards and analytics that tolerate hourly latency
Stack
dbtFivetranAirflowSnowflakeBigQuery
Nightly Pipeline Run
Extract
Postgres · Shopify · Salesforce · GA4
Transform
dbt models · deduplication · joins
Load
Snowflake · BigQuery · Redshift
2 hr
Run time
99.9%
Uptime
150+
Pipelines
Our ProcessFrom scattered data to
From scattered data to
living dashboards
Every engagement follows a four-stage process engineered around one outcome: business teams making confident decisions from live data.
Data audit to architecture design1–2 weeks
Full pipeline and dashboard build6–12 weeks
Training, docs, and handover1 week
01
Data Audit
We assess your current data sources, quality, and infrastructure — and identify the biggest gaps and opportunities before touching a line of code.
02
Architecture Design
We design your data stack: ingestion, storage, transformation, and visualisation layers aligned to your scale and query patterns.
03
Build & Integrate
We build pipelines, dashboards, and models — integrating with your existing tools and systems without disrupting operations.
04
Train & Handover
Full documentation, team training, and optional ongoing support to keep your data stack healthy and evolving as you grow.
The Business Case
Unified Stack vs Data Silos
The cost of fragmented data compounds with every new tool you add. The case for unification is concrete.
| Criterion | Unified Data Stack | Data Silos |
|---|---|---|
| Data freshness | Minutes or real-time | 24–72 hrs (manual export) |
| Source of truth | One warehouse, one metric | Each tool has its own number |
| Cross-system analysis | Join any two datasets | Manual spreadsheet merge |
| Executive reporting | Live self-serve dashboard | 8 hours of weekly prep |
| Data quality validation | dbt tests on every run | No automated validation |
| Historical trend depth | 3+ years, any granularity | Limited to tool retention |
| Analyst onboarding | SQL + documented model | Weeks learning 7+ tools |
Client Outcome
7 systems → one live warehouse
Challenge
D2C brand had revenue data spread across Shopify, Klaviyo, Meta Ads, Google Analytics, and WooCommerce — no unified view of CAC or true margin per channel.
What We Built
Snowflake warehouse with dbt transforms, Fivetran connectors for all 5 sources, and Looker dashboards for finance, marketing, and ops — live, in 8 weeks.
Results
Live daily
CEO reviews live P&L (was weekly)
+18%
Gross margins from CAC visibility
Weekly
Inventory decisions (was quarterly)
Ready to unify your data?
Talk to an engineer this week — not a sales rep. We'll map out a real data strategy for your stack.
Industries
Analytics across every vertical
E-Commerce & Retail
+18% marginBasket analysis · Inventory forecasting · CLV
SaaS & Tech
-22% churnChurn prediction · Feature adoption · MRR analytics
Healthcare
30% cost savingPatient outcomes · Operational efficiency · Compliance
BFSI
-35% defaultsRisk scoring · Fraud detection · Regulatory reporting
Logistics
+25% on-timeRoute optimisation · Delivery SLA · Fleet analytics
Manufacturing
-50% downtimeOEE · Predictive maintenance · Supply chain
"We had data in 7 systems and no way to see the full picture. Ethersofts built our warehouse and dashboards in 8 weeks — now every Monday meeting runs on live data instead of stale spreadsheets."
SA
S. Al-Farsi
COO, D2C Brand · Dubai
Tech Stack
Tools we build with
SnowflakeBigQueryRedshiftdbtApache SparkKafkaAirflowFivetranPower BITableauLookerMetabasePythonSQLDatabricks
FAQ
Questions we get all the time
If yours is not here, reach out. We respond within 24 hours with a real answer from an engineer — not a sales pitch.
Yes. Data unification is one of our core offerings. We connect CRMs, ERPs, databases, APIs, spreadsheets, and SaaS tools into a single warehouse, then layer clean dashboards on top.
We are platform-agnostic. We build in Power BI, Tableau, Looker, Metabase, and Grafana — or custom-built React dashboards if you need a white-labelled analytics product.
A focused dashboard on cleaned data can go live in 2–3 weeks. Full data warehouse setup with pipelines for a mid-size company typically takes 6–12 weeks.
Both. We offer retainer-based data engineering support for teams that want to continue building on their data stack after initial delivery.
We implement encryption at rest and in transit, role-based access controls, data masking for PII, and audit logging. All infrastructure is configured to your compliance requirements.
Both. We build scheduled batch ETL with dbt and Airflow for analytics that tolerate hourly latency, and real-time streaming pipelines on Kafka and Flink for fraud detection, live personalisation, and operational dashboards with sub-second freshness. We also build CDC (Debezium) and reverse-ETL pipelines to keep your warehouse and business tools in sync.
A focused dashboard on already-clean data starts around $6k–$12k. A full data warehouse with pipelines, dbt models, and dashboards for a mid-size company typically runs $25k–$70k depending on the number of sources and transformation complexity. We give a fixed quote after a free data audit so there are no surprises.
Data AnalyticsMake your data
Make your data
actually usable
Tell us where your data lives. We will build the pipelines, warehouse, and dashboards that turn it into reliable answers.
Free consultation24-hour responseNDA on request