Data &

Data will talk if you're ready to listen.

Many organisations face challenges in unlocking the full potential of their data due to inflexible architectures, poor organisational adoption and readiness, costly licensing environments, and overall lack scalability. Versent Data & Insights assists you in overcoming these obstacles, empowering you to provide meaningful, trusted and actionable analytics for your organisation. This ensures that your data supports your digital agenda, helping you make better decisions to grow your business.

Our expertise

The deep analysis transit data allows our customers to understand what’s going on in their operations in real-time and how riders are using the transit network and changing patterns of usage over time. Customers can now make informed decisions on the live, clean data.

Sean Langton, CTO, Vix Technology

Evolve your modern data ecosystem

  • 01


    Migrate data from legacy Oracle and SQL Server platforms to the cloud.

  • 02


    Bespoke agile data platforms (warehouses, lakes, lakehouses, data hubs), Application DevOps, DataOps and automation, fully integrated products (such as data mesh, semantic knowledge graphs).

  • 03


    Full analytics integration, IoT and digital twinning, ML Ops.

  • 04


    Data BAU uplift, data platform; SRE management.

Our data & insights team comprises over 50 data engineers and scientists, with certifications in AWS, Azure, Snowflake, Databricks, Fivetran, DBT and other leading ISV providers. Our team has experience in data engineering, data analysis, modelling, and advanced analytics. We augment our customer teams with multi-disciplinary capabilities across an array of industry verticals and solution areas.

  • 200% Increased delivery velocity
  • 50+ Data engineers & scientists
  • 30+ Certificates

Our success stories

Our proven and battle-tested approach translates into accelerated outcomes: a modern data foundation built in weeks, not months or years, and better delivery velocity and reliability via automation and modern AnalysisOps, DataOps, MLOps best practices.