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Data Engineering Services
Your IT Data Is a Strategic Asset. Start Treating It Like One.
Turn scattered, untrusted IT data into a single source of truth that powers AI, automation, and faster decisions.
Proven Impact Blueprint
A 360-degree, catalog-based IT data analysis to discover insights and solutions that address real business problems.
Deep Tech & Domain Expertise
We are IT-domain and deep-tech experts who work fluently across any stack.
Data Quality & Trust Controls
Built-in validation and governance frameworks ensure accuracy, consistency, and reliability — making your data AI-ready.
Vendor-Agnostic by Design
Customer-first, independent technology selection with no lock-in. We pick the right tools for your environment to cut cost and keep you flexible, so every downstream decision rests on data you can trust.
Proven enterprise data outcomes
Less operational toil
Event-driven automation replaces manual polling & checks
Duplicate data reduced
Account data deduplicated & cleansed at enterprise scale
Hours saved
Employee downtime eliminated through AI-driven documentation
Data accuracy
Real-time asset sync with zero manual reconciliation
Delivery & readiness proof
To demonstrated business value
Agile sprint cadence
Asset & data visibility
Inventory record accuracy
AI skills & agents in production
The data trust gap
Why does enterprise IT data break at scale?
Volumes of IT data are generated every second, but most of it remains untapped, unstructured, or untrustworthy. Across industries, four barriers keep showing up.
Data Trapped in Silos
68% of organizations cite data silos as their #1 concern, up 7% year-over-year.
Fragile Pipelines & Wasted Effort
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37% of data leaders spend most of their time on maintenance and “keeping the lights on,” rather than innovation.
Governance Gaps & Trust Deficit
Poor data quality costs organizations an average of $12.9M annually, while 80% of governance initiatives are likely to fail by 2027.
Insights Arrive Too Late
By the time traditional reports are finalized, the window to act has already closed.
Capabilities
A holistic approach across your entire data lifecycle
From first catalog to long-term governance, Astreya assesses, executes, and runs your IT data estate so it stays trustworthy as it grows.
Assess
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Catalog your data sources, benchmark data quality and AI readiness, and identify AI solutions that align with your specific business goals.
- Data source cataloging across ITSM, assets & telemetry
- Data quality & AI-readiness benchmarking
- Data quality score
- Enterprise data blueprint
- Implementation roadmap
8-week proof of concept • Low-risk pilot, tailored to your stack
Execute
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Deliver robust ETL pipelines, actionable insights, and custom AI solutions in agile 4-week sprints — with transparent Show & Tell checkpoints at every milestone.
- Robust, validated ETL pipelines
- Custom AI solutions & actionable insights
- Agile 4-week sprint delivery
- Show & Tell checkpoints at every milestone
- Raw data translated into discoverable knowledge
8-week proof of concept • Low-risk pilot, tailored to your stack
Run & Transform
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Set up and maintain IT master data management, and enforce AI-ready data governance frameworks that keep your foundation stable for the long term.
- IT master data management (MDM)
- AI-ready data governance frameworks
- Ongoing compliance & audit-ready lineage
- Continuous efficiency improvements
- Long-term infrastructure stability
8-week proof of concept • Low-risk pilot, tailored to your stack
Operational methodology
Built for trust, not just throughput.
How we turn fragmented IT data into a foundation your teams — and your AI — can rely on.
Unified Data Foundation
We catalog and integrate scattered IT sources — tickets, assets, telemetry, monitoring, and cloud platforms — into one trusted, queryable foundation.
Validation at Every Layer
Data quality frameworks enforce accuracy and consistency at ingest, transform, and delivery, so pipelines fail loudly instead of quietly corrupting reports.
Governance by Design
AI-ready governance, master data management, and clearly defined roles are built in from day one — not retrofitted after an audit.
Show & Tell Transparency
Every 4-week sprint ends in a working demonstration on your own data, so progress is visible and priorities can shift without losing time.
Knowledge Compounding
Semantic models and structured documentation turn raw data into discoverable knowledge that makes each subsequent use case faster to deliver.
Insight at Decision Speed
Dashboards and AI agents surface anomalies, trends, and answers in real time — so teams act while the window to act is still open.
Why Astreya
A data partner accountable for outcomes
Managed data engineering delivered the way IT actually works. Evidence first, governance built in, and no dependency on any single vendor's stack.
Start from the answer
We skip the theory and build around proven outcomes: 85% less operational toil, 74% less duplicate data, and 40,000 hours saved. Then, we map the shortest route to get you the same results.
IT-native specialists
Our engineers understand the actual IT estate—ITSM, assets, telemetry, and monitoring—not just generic data tools. That domain context is why our pipelines work on day one.
Trust, engineered in
From automated validation frameworks and MDM to audit-ready governance with clear data lineage: we ensure every downstream decision rests on verified, defensible data.
No lock-in, ever
Vendor-agnostic by design. We maximize the value of your existing IT investments and architect around the stack you already own, rather than imposing a costly rip-and-replace.
Ecosystem integrations
Works with the stack you already run
Vendor-agnostic engineering inside your current stack: data platforms, pipelines, BI tools, and ITSM. Zero rip-and-replace.
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Data Platforms
- Hadoop
- Apache Hive
- MySQL / SQL
- Amazon Redshift
02
Pipelines & Code
- Python
- Apache Airflow
- SAS DataFlux
- UiPath RPA
03
BI & Visualization
- Tableau
- Power BI
- Looker Studio
- Plotly / Deneb
04
ITSM & Ops
- ServiceNow
- Jira
- ITGlue
- Oomnitza
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AI & LLMs
- Claude
- Gemini
- Now LLM
- Workflow Data Fabric
Engagement & delivery
Start small, win fast, minimize risk
Prove value in 8 weeks with a low-risk pilot tailored to your environment. Then scale on your terms.
Data maturity assessment
4-week assessment
Stop guessing what your IT data estate looks like. We map, profile, and correlate every tool and dataset you run, handing you a validated maturity score, clear gap analysis, and an immediate execution roadmap.
Proof of concept
8-week pilot
We baseline your IT data estate, score quality and AI readiness, and stand up a production-tailored proof of concept that proves hard business impact in your actual stack.
Program delivery
Sprint-based build
We execute in agile four-week sprints to ship production pipelines, operational insights, and custom AI solutions. Every milestone features hands-on Show & Tell reviews. Your priorities steer every build.
Managed operations
Run & transform
Most teams build the foundation, hand you the keys, and walk away. We run it. We evolve it. Master data management. AI-ready governance. Compliance that doesn't slip with efficiency that stacks up over time.
Proof in action
Enterprise data results that speak for themselves
How global IT leaders partner with Astreya to consolidate data, automate the toil, and put AI on a foundation it can trust.
85% less operational toil. 10+ AI agents in production.
Poor data quality, manual oncall and triage, and tribal knowledge eroded engineer trust. Astreya unified topology data into a reliable ODS on Hive, built Data Marts with a flexible Tableau framework, and encoded triage and debugging runbooks into autonomous AI agents built with Claude.
Proactive failure detection · Tribal knowledge codified into AI runbooks · AI-ready codebase
85%
Reduction in operational toil via event-driven AI automation
10+
AI skills & agents: code review, oncall monitoring, triage, briefings
Social networking platform
Engineer dispatch, optimized by model.
A heatmap and agglomerative clustering model, a weekly custom data pipeline, and Tableau dashboards replaced manual, high-cost engineer dispatch across worldwide PoP locations.
Reduced resolution time & travel costs · Model extended globally
Global
Model extended globally
Weekly
Custom data pipeline
AI-optimized engineer deployment
74% less duplicate account data.
20+ disconnected source systems and mismatched commodity codes gave way to a robust vendor data model, redesigned governance, and an MDM roadmap on SAS DataFlux.
74% less duplicate account data · Stronger compliance & spend visibility
74%
Less duplicate account data
20+
Disconnected source systems
Vendor master data, unified
Response time performance from 58.2% to 98%.
An overhaul of dashboards and metrics plus AI-driven documentation lifted response time performance from 58.2% to 98% and cut ticket backlog by 51%.
40,000 hours of downtime saved · MTTR improved 81%
98%
Response time performance
51%
Ticket backlog cut
Dashboards that changed decisions
Build time cut from months to days.
An automated CI/CD pipeline governed by simple YAML configs migrated dashboards, matched Tableau's customization with Plotly and Deneb, and cut refresh latency with Redshift.
Near real-time dashboards · Solution build time cut from months to days
Days
Solution build time cut from months to days
Real-time
Near real-time dashboards
Tableau to Power BI, without the pain
Insights & thought leadership
Go deeper into the future of IT data
Strategic frameworks and operating models from Astreya's data and AI transformation leaders.
Why the Future of BI Is Adaptive Decision-Making
Static reports arrive after the window to act has closed. What it takes to move from rear-view dashboards to decisions made at operational speed.
Read article →
Why In-House Teams Struggle to Bridge the AI ROI Gap
Most AI initiatives stall on the same hidden dependency: the data underneath. Why capable teams still miss the return — and what closes the gap.
Read article →
Active Metadata: The Operating Layer Enterprise AI Is Missing
AI agents can't operate on data they can't understand. How active metadata becomes the connective layer between your systems and your AI.
Read article →Data Engineering FAQ
Frequently asked questions
Everything you need to know about our approach, deliverables, and how we work with the stack you already own.
Have a specific question?
Our data engineering specialists are available to review your current data landscape, tooling, and AI-readiness requirements.
What is IT data engineering?
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IT data engineering is the practice of collecting, integrating, and governing the data your IT estate generates — tickets, assets, telemetry, monitoring, and cloud platforms — so it becomes a single trusted source that supports reporting, automation, and AI. Astreya delivers it as a managed service across three phases: Assess, Execute, and Run & Transform.
How quickly can we see value?
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A four-week maturity assessment gives you a baseline: an IT data maturity score, a gap analysis, and a prioritized roadmap. From there, an eight-week pilot demonstrates measurable business value on your own data before you commit to a broader programme. Ongoing delivery then runs in agile four-week sprints, each closing with a Show & Tell on live data.
Do we have to replace our existing data tools?
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No. Our approach is vendor-agnostic by design. We work inside the platforms you already run — including ServiceNow, Databricks, Tableau, Power BI, Looker Studio, Hadoop, Hive, and more — with independent, customer-first technology selection and no lock-in. Our accelerators are built on open technologies and standards, are modular, and coexist with your existing stack.
How do you make our data AI-ready?
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We benchmark data quality and AI readiness up front, build validation frameworks that enforce accuracy and consistency, add semantic models and structured documentation, and put AI-ready governance in place — so AI agents and analytics operate on data you can trust.
What deliverables should we expect?
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Assess produces a data quality score, enterprise data blueprint, and implementation roadmap. Execute delivers robust ETL pipelines, actionable insights, and custom AI solutions. Run & Transform provides ongoing compliance, continuous efficiency improvements, and long-term infrastructure stability.
Do you handle data governance and compliance?
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Yes — governance is built in from day one rather than retrofitted after an audit. We set up and maintain IT master data management with defined roles, standards and programme governance, and deliver audit-ready lineage so every downstream decision can be traced back to its source. Continuous governance then keeps accuracy, consistency and compliance holding as the estate grows.