Data Analytics & BI

To turn data into decisions, you need a stack that can ingest, transform, store, and serve — reliably and at the speed your business actually moves. The 2026 toolkit is mostly off-the-shelf: cloud warehouses (Snowflake, BigQuery, Databricks, Redshift), ELT pipelines (dbt, Fivetran, Airbyte), orchestration (Airflow, Dagster, Prefect), and visualization (Tableau, Power BI, Looker, Metabase, Superset).

We architect, ship, and operate that stack for SMEs and startups — picking the components that fit your budget and team size, not the most expensive ones. Custom platforms still make sense when the off-the-shelf tools don't bend far enough; see how a Swiss accounting firm built theirs with us.

Dashboards turn raw rows into decisions. We design them on the tool that fits your team — Tableau, Power BI, Looker, Metabase, Superset, or Google Looker Studio — and ground them in a semantic layer (dbt Semantic Layer, Cube, LookML) so every chart speaks the same definitions of revenue, churn, and MRR.

Whatever the tool, the dashboards we ship include:

• multiple source connectors (Excel, CSV, databases, SaaS APIs)
• secure web access with role-based permissions and row-level security
• embeddable reports for portals and partner apps
• self-service exploration so non-specialists can answer their own questions

For use cases where yesterday's data isn't fast enough, we build streaming pipelines (Kafka, Flink, Snowflake streaming, ClickHouse) and lakehouse architectures (Databricks, Iceberg, Delta Lake) so analytics and operational systems share the same trustworthy source of truth.

This unlocks fraud detection that fires on the next transaction, dashboards that refresh on event arrival rather than nightly batches, and reverse-ETL flows (Hightouch, Census) that push analytics insights back into Salesforce, HubSpot, or your own product.

Search and retrieval is where data meets users. For structured catalogues (e-commerce, document libraries, internal wikis) we build keyword + faceted search on OpenSearch, Elasticsearch, or Meilisearch. For semantic and RAG use cases, we layer vector databases (pgvector, Qdrant, Weaviate, Pinecone) and the embedding pipelines that keep them fresh.

Our in-house engine Sevtin packages this into a turnkey full-text search for e-commerce catalogues — it indexes your product database automatically and returns sub-second relevant results without your team having to stand up a search infrastructure from scratch.

More details at our Data Analytics & BI Consulting page.