Astrea IT Services
Official Databricks Partner
2026

Data Intelligence,
Engineered
for Business.

Astrea IT Services helps organisations build unified, governed data platforms on Databricks — turning fragmented data into competitive intelligence.

Official Partner · Active
PlatformDatabricks Lakehouse
Clouds SupportedAWS · Azure · GCP
Faster Insights Average
Records / Day10B+ at Scale
Partner Since2026
As a certified Databricks partner, Astrea IT Services delivers end-to-end Lakehouse implementations — from architecture design and data engineering to ML platforms and ongoing optimisation.
10B+
Records Processed Daily
Faster Business Insights
40%
Reduction in Data Costs
60+
Native Integrations
One Platform.
Every Data Workload.
Databricks Lakehouse Architecture
🗄️
Delta Lake
Open storage · ACID transactions · Schema enforcement · Time travel
Storage
Apache Spark
Distributed compute · Batch & streaming · Petabyte-scale processing
Compute
🤖
MLflow + AutoML
Model lifecycle · Experiment tracking · Production deployment
AI / ML
🛡️
Unity Catalog
Data governance · Lineage tracking · Fine-grained access control
Governance
📊
SQL Analytics
Serverless SQL · BI dashboards · Native connector ecosystem
Analytics
01 /

One platform replacing five

Databricks consolidates your data warehouse, ETL tool, ML platform, BI layer, and governance system into a single Lakehouse — eliminating data silos at the foundation.

02 /

Cloud-native and infinitely scalable

Run on AWS, Azure, or GCP with autoscaling clusters. Whether you're processing millions or billions of records, Databricks scales without manual infrastructure management.

03 /

AI and data in the same workspace

Engineers, scientists, and analysts collaborate in one environment. No data movement, no handoffs, no delays between data preparation and model deployment.

04 /

Open by design, never locked in

Built on open standards — Delta Lake, Apache Spark, MLflow. Your data, models, and pipelines remain portable and vendor-independent.

Full-Spectrum Data Intelligence.

From raw ingestion to production AI — Databricks covers the complete data lifecycle, and Astrea IT implements all of it.

🔄
01 — Data Engineering

Pipelines & ETL

Build robust, scalable data pipelines using Delta Live Tables, Auto Loader, and Structured Streaming — processing batch and real-time data with unified orchestration.

Delta Live TablesAuto LoaderStreaming
🤖
02 — Machine Learning

ML & AI Platform

Build, track, and deploy models at scale with MLflow and Feature Store. Serve predictions in real time or batch with governed Model Serving endpoints.

MLflowFeature StoreAutoML
📊
03 — Analytics

SQL & BI

Run fast, serverless SQL on your Lakehouse. Connect Power BI, Tableau, or Looker — all querying the same governed, unified data layer.

Serverless SQLPower BITableau
🛡️
04 — Governance

Unity Catalog

Fine-grained access control, data lineage, audit logging, and compliance tooling across all data assets — tables, models, notebooks, and files.

Unity CatalogLineageRBAC
🧠
05 — Generative AI

LLMs & RAG

Fine-tune and serve large language models on your proprietary data. Build intelligent RAG applications and AI assistants with full governance and lineage.

LLM Fine-tuningRAGAI Functions
☁️
06 — Infrastructure

Multi-Cloud

Deploy on AWS, Azure, or GCP with consistent tooling. Migrate between clouds or run multi-cloud workloads without re-engineering pipelines.

AWSAzureGCP
What Businesses Build
With Databricks.
📈

Customer Analytics & 360°

Unify customer data from CRM, marketing, support, and product into a single Customer 360 — enabling personalisation and churn prediction at enterprise scale.

  • Unified customer profiles across all touchpoints
  • Real-time segmentation and personalisation
  • ML-powered churn prediction and early warning
🏭

Operational & IoT Intelligence

Process sensor, machine, and operational data in real time — powering predictive maintenance, quality control, and supply chain optimisation.

  • Predictive maintenance reducing unplanned downtime
  • Real-time anomaly detection on equipment data
  • Demand forecasting across the supply chain
💰

Financial Risk & Compliance

Run risk models, fraud detection, and regulatory reporting on a fully governed data platform with complete audit lineage and access controls.

  • Real-time fraud detection pipelines
  • Regulatory reporting with full data lineage
  • Credit risk scoring models at scale
🧬

AI-Powered Product Features

Embed intelligence directly into your product — recommendation engines, LLM-powered features, and real-time ML serving on the Lakehouse.

  • Recommendation engines trained on live data
  • LLM applications on proprietary company data
  • Real-time feature serving for production ML
What Astrea IT Delivers.

End-to-end Databricks implementation — from first design to live production and beyond.

01

Lakehouse Architecture & Design

Design your Databricks Lakehouse from the ground up — data zones, Delta Lake structure, cluster policies, and governance model built for your specific workloads.

ArchitectureDelta Lake
02

Data Pipeline Implementation

Build production-grade ETL and ELT pipelines using Delta Live Tables and Auto Loader — from raw ingestion to gold-layer tables ready for analytics and ML.

ETL / ELTDLT
03

Cloud Migration to Lakehouse

Migrate from legacy warehouses, Hadoop clusters, or fragmented cloud environments to a unified Databricks Lakehouse with structured, minimal-disruption methodology.

MigrationHadoop
04

ML & AI Platform Setup

Configure MLflow, Feature Store, and Model Serving — creating a governed, reproducible ML environment from experimentation through to production deployment.

MLflowDeployment
05

Unity Catalog & Governance

Implement organisation-wide data governance — workspaces, metastores, RBAC policies, data lineage, and audit logging across all data assets and teams.

Unity CatalogRBAC
06

Training, Support & Optimisation

Role-based training for engineers, analysts, and scientists. Ongoing performance optimisation, cost management, and managed support as your platform scales.

TrainingSupport
Works With Your
Existing Stack.

Native connectors across cloud, BI, orchestration, and streaming — no rip-and-replace required.

Category Tools & Platforms Integration Type
Cloud
AWSMicrosoft AzureGoogle Cloud
Native deployment, managed clusters, IAM integration
BI & Reporting
Power BITableauLookerQlik
SQL connector, Partner Connect, direct query mode
Orchestration
Apache AirflowAzure Data FactoryPrefect
Databricks operator, REST API, job clusters
Streaming
Apache KafkaAzure Event HubsAWS Kinesis
Structured Streaming, Auto Loader, triggers
Transformation
dbtDelta Live TablesSQL
dbt-databricks adapter, native DLT pipelines
CRM & Enterprise
SalesforceSAPWorkday
Partner Connect, REST connectors, JDBC/ODBC
Built for Teams Serious
About Data.
📉

CDO / Data Leaders

Data Strategy
  • Data siloed across warehouses, lakes, and spreadsheets with no single source of truth
  • Need enterprise-grade governance without slowing down data teams
  • Want self-service analytics without losing control of quality
  • Looking to reduce time-to-insight from months to days
⚙️

Data Engineers

Engineering & Pipelines
  • Maintaining fragile pipelines that break when source schemas change
  • Want Delta Live Tables to handle monitoring and error recovery automatically
  • Need unified streaming and batch in one codebase, not two
  • Looking to dramatically reduce pipeline maintenance overhead
🧪

Data Scientists & ML Teams

AI & Machine Learning
  • Models take weeks to deploy due to disconnected infrastructure
  • Need experiment tracking, feature reuse, and reproducibility in one workspace
  • Want to build LLM-powered features on proprietary company data
  • Looking to shorten the model-to-production cycle significantly
From Discovery
to Production.
01
Discovery & Assessment
We review your current data sources, infrastructure, team structure, and business goals — identifying the fastest, cleanest path to a Databricks Lakehouse.
02
Architecture Design
We design your Lakehouse blueprint — data zones, pipeline topology, Unity Catalog structure, cluster policies, and cloud environment configuration.
03
Build & Migrate
We implement pipelines, migrate historical data, configure Unity Catalog, and set up ML environments in structured sprints with clear milestones.
04
Validate & Train
End-to-end data quality validation, performance testing, and role-based training for engineers, analysts, and scientists before go-live.
05
Scale & Optimise
Go live with dedicated hypercare support. Followed by ongoing cost optimisation, query performance tuning, and platform evolution as your data grows.