DevQore

Data Services

From raw data to trusted insight

We design data platforms, pipelines and dashboards that give your teams one reliable source of truth, with the quality, lineage and governance regulated industries need, and a solid foundation for AI.

One trusted source of truth

Automated, monitored pipelines

Self-service dashboards

Governance built in

Talk to our data team Read: is your data AI-ready?

What we deliver

Data engineering, analytics and governance

Build the platform once, and every team benefits.

Data engineering and pipelines

Reliable ETL and ELT pipelines that move data on schedule and alert you when something breaks.

  • Batch and streaming pipelines
  • Source-system integration
  • Pipeline monitoring and alerting

Fresh, reliable data every day

Data warehouse and lakehouse

A modern, scalable home for all your data.

  • Warehouse and lakehouse design
  • Data modelling for analytics
  • Migration from legacy databases

One source of truth for the whole company

Business intelligence and analytics

Dashboards and reports people actually use.

  • KPI design with business teams
  • Interactive, self-service dashboards
  • Embedded analytics in your apps

Faster, better-informed decisions

Big data and real-time processing

Process large and fast-moving data at scale.

  • Distributed processing with Spark
  • Real-time streaming analytics
  • Cloud-native, cost-efficient design

Insight from data at any volume

Data governance and compliance

Know where your data is, who can see it and how it is used.

  • Access controls and data catalogues
  • Lineage and data quality checks
  • Privacy and retention policies

Trusted data and smoother audits

Data for AI and machine learning

Prepare the data your AI and ML use cases depend on.

  • Feature and training data pipelines
  • Document and knowledge-base preparation for RAG
  • Data readiness assessment

AI projects that start on solid ground

Next step: AI

Ready to put your data to work with AI?

Once your data is trusted, our AI team can turn it into forecasting, automation and generative AI tools.

How we work

How we build your data platform

Value early, then a platform that grows with you.

01

Assess

1 to 2 weeks
  • Data sources and quality review
  • Reporting needs
  • Target architecture
02

Build

4 to 8 weeks
  • Pipelines and warehouse
  • Core data models
  • First dashboards
03

Scale

Ongoing
  • More sources and use cases
  • Self-service analytics
  • Performance tuning
04

Govern

Ongoing
  • Access and quality controls
  • Lineage and catalogue
  • Monitoring and support

By industry

Data for your industry

Technology

Data tools and platforms we use

Snowflake Databricks Amazon Redshift Google BigQuery Azure Synapse Apache Spark Apache Kafka Airflow dbt PostgreSQL Power BI Tableau Looker

FAQ

Questions we often hear

What is the difference between a data warehouse and a data lakehouse?

A warehouse stores structured, modelled data for reporting. A lakehouse adds low-cost storage for raw data, so analytics and machine learning share one platform.

How long does it take to build a data platform?

A first version with core pipelines and dashboards often takes a few weeks to a couple of months, then grows over time.

Which BI tool should we use?

It depends on your users and existing stack. We work with Power BI, Tableau, Looker and others.

Can you work with our existing databases?

Yes. We connect to your current systems and can migrate them to a modern platform step by step.

From our blog

Is Your Data Ready for AI? 6 Tests Every Data Platform Must Pass

Read the article

Need a data platform you can trust?

Tell us what you need. We’ll reply within one business day.

Contact us Email sales@devqore.io