We consolidate your scattered data sources into unified analytics platforms that executives actually use — real-time dashboards, self-service BI, and predictive insights built on production-grade data pipelines. From data warehousing and ETL to advanced visualization, we connect your Oracle, SAP, Salesforce, and custom systems into a single source of truth.
In tech, true autonomy strengthens bonds. By transferring knowledge and best practices, we enable independence while forging long-term partnerships, earning the trust of Europe's premier organizations.
Most enterprise dashboards lie by omission. Numbers are 24 hours old, definitions drift between departments, and the one report leadership actually needs requires a week of manual spreadsheet work. DNA Solutions builds analytics on top of properly engineered data pipelines, so the metrics you see at 9am reflect what happened at 8:55am — with consistent definitions across every team. 20 years of building enterprise data infrastructure means we know where the foundations break before they do.
From data warehousing to executive dashboards, we cover the full analytics stack — always grounded in reliable data engineering.
Modern data warehouses and lakehouses built on Snowflake, BigQuery, Databricks, or your existing infrastructure. We design schemas that scale, model business domains correctly, and stay performant as data volumes grow.
We handle the full lifecycle: ingestion from operational systems, transformation layers, semantic modeling, and governance. The result is one trusted source of truth your analysts and BI tools can rely on without manual reconciliation.
Executive dashboards and operational reporting in Power BI, Tableau, Looker, or Metabase — connected to live data, not yesterday's extracts. Drill-downs that work, definitions that match across teams, and performance that holds up under load.
We focus on the decisions each dashboard supports, not the chart count. Every metric is traceable back to source systems, with documented business logic so finance, ops, and product all see the same numbers.
Production-grade pipelines that move data from Oracle, SAP, Salesforce, and legacy systems into your analytics platform — batch, micro-batch, or real-time streaming depending on what each use case actually needs.
Our pipelines handle schema drift, failed loads, and late-arriving data without silent failures. Monitoring, lineage, and data quality checks are built in, so when a number looks wrong, you can trace it to the row that caused it.
Semantic layers and governed datasets that let business teams answer their own questions without breaking things. Role-based access, certified metrics, and clear ownership for every data domain.
We set up the guardrails — data catalogs, definitions, lineage, access controls — so self-service doesn't turn into a hundred conflicting versions of revenue. Less ticket queue, more decisions made in the meeting.
Analytics investments only pay off when the underlying data is trustworthy. Here's how we approach the most common concerns.
Not always. We assess your existing landscape first. Sometimes a lakehouse on top of current systems delivers more value than a full migration. We recommend consolidation only when the operational cost of fragmentation exceeds the cost of moving.
We build a semantic layer with certified metrics — one definition of revenue, churn, or margin that every tool reads from. Combined with a data catalog and clear ownership, departments stop arguing about whose number is right.
Yes. We're tool-agnostic and have delivered on Power BI, Tableau, Looker, Metabase, Qlik, and custom front-ends. The platform matters less than the data model underneath it, which is where we focus first.
A first set of certified dashboards on top of one or two key domains typically ships in 6-10 weeks. Full enterprise rollout depends on source-system complexity, but we deliver incrementally so leadership sees value before the program ends.
Every pipeline includes automated quality checks: schema validation, freshness monitoring, null and range tests, and reconciliation against source systems. Issues are flagged before they reach dashboards, with clear ownership for resolution.