Business Intelligence Services
StepTo builds custom BI and data analytics solutions, dashboards, data warehousing, and self-service analytics, at 40-60% lower cost than local hiring.
Reviewed by Igor Gazivoda, Co-founder & CEO of StepTo · Updated
StepTo turns operational data, sales, finance, product, marketing, into dashboards and reports that people actually trust and use. We design and build complete BI stacks: data ingestion, warehousing, a governed transformation layer, and the dashboards on top, as part of our custom software development services. Our engineers in Serbia (a national talent pool of 60,000+ IT professionals) deliver BI and analytics engineering at $35–75/hr for most delivery work, 40–60% below Western European or US consultancies.
What Business Intelligence Services Do We Deliver?
- Data warehouse design & build: Snowflake, BigQuery, Redshift, or PostgreSQL warehouses with dimensional or wide-table modelling suited to your query patterns and budget.
- Data pipeline engineering: Ingestion from operational databases, SaaS tools (CRM, billing, marketing), and files via Airbyte, Fivetran, or custom connectors, with dbt-based transformation and testing.
- Dashboard development: Executive scorecards, operational dashboards, and financial reporting in Power BI, Tableau, Looker, Metabase, or Superset.
- Semantic layer & KPI governance: Single, tested definitions for core metrics so every report shows the same number for the same question.
- Embedded & customer-facing analytics: In-product dashboards for SaaS companies with multi-tenant security and sub-second serving layers.
- Predictive analytics: Forecasting, churn scoring, and anomaly detection built into the reporting stack where the data supports it.
- BI stack audits: Review of an existing warehouse and report estate, cost, performance, metric consistency, with a prioritised remediation plan.
Which Tools Make Up a Cost-Conscious BI Stack?
- Ingestion: Airbyte, Fivetran, or custom Python/Node connectors for proprietary systems
- Warehouse: Snowflake or BigQuery for elastic scale; ClickHouse or PostgreSQL where licence and compute costs must stay minimal
- Transformation: dbt with version control, automated tests, and documented lineage
- Visualisation: Power BI, Tableau, Looker, or open-source Metabase/Superset to avoid per-seat licensing
- Orchestration & quality: Airflow or Dagster scheduling, freshness monitoring, and alerting on failed loads
Which Engagement Model Fits Your BI Programme?
- Fixed-scope BI project: Warehouse, pipelines, and an agreed dashboard set, typically $20,000–200,000 depending on source count and complexity. Rates $35–75/hr for most delivery work; see pricing.
- Staff augmentation: Analytics engineers or BI developers embedded with your team from $4,500/month per engineer.
- Dedicated analytics team: From $13,500/month, data engineering, modelling, and dashboarding as a continuous capability.
Why Choose StepTo for Business Intelligence?
- Engineering rigour: Version-controlled models, automated tests on metrics, and CI for the data stack, BI treated as software, not as a pile of reports.
- Licence-aware recommendations: We optimise total cost including warehouse compute and BI seats, and are equally comfortable in commercial and open-source tools.
- Adoption focus: Dashboards are designed with the people who will use them; a report nobody opens is a failed project regardless of its architecture.
- CET timezone: Same-day iteration with European teams and 3-4 hours of overlap with US East Coast stakeholders.
How Does a BI Project Run?
- Discovery (1–2 weeks): Key decisions the business needs data for, source-system inventory, and definition of the first KPI set.
- Stack selection & architecture: Warehouse, ingestion, and BI tool choices with a total-cost projection.
- First dashboards live (4–8 weeks): One or two sources modelled end-to-end so stakeholders see real value early.
- Expansion: Additional sources, the governed semantic layer, and self-service enablement for analysts.
- Operations: Freshness monitoring, cost tuning, and a managed request backlog under an ongoing engagement.
What Do Analytics Leaders Ask Before a BI Build?
- How much do business intelligence services cost?
- A departmental BI setup, one data source consolidated into a warehouse with a set of Power BI or Metabase dashboards, typically costs $20,000–50,000 over 6–10 weeks. A company-wide analytics platform with a governed warehouse (Snowflake/BigQuery), dbt transformation layer, and self-service semantic model usually runs $60,000–200,000 over 3–9 months. StepTo engineers bill $35–75/hr for most delivery work, roughly 40–60% below Western European or US data consultancies.
- Which BI tools do you work with?
- Power BI, Tableau, Looker, Metabase, and Apache Superset on the visualisation side; Snowflake, BigQuery, Redshift, ClickHouse, and PostgreSQL as warehouses; dbt for transformation; and Airbyte or Fivetran for ingestion. Tool choice follows your licensing budget and team skills, Metabase or Superset can save five figures a year in licence fees for smaller teams, while Power BI is usually right for Microsoft-centric organisations.
- Our reports disagree with each other. Can you fix that?
- This is the most common reason clients call us. Conflicting numbers almost always trace back to metric definitions living inside individual reports instead of a shared layer. We fix it by building a governed transformation layer (dbt) and a semantic model where each KPI, revenue, churn, margin, is defined once, tested automatically, and consumed by every dashboard from the same source.
- Can you embed analytics into our SaaS product?
- Yes. We build customer-facing analytics with embedded BI (Power BI Embedded, Looker Embedded, Metabase embedding) or fully custom React dashboards over a fast serving layer such as ClickHouse. Multi-tenant row-level security is designed in so each customer sees only their own data, and we load-test against your largest tenant before launch.
- Do you provide ongoing BI support after the initial build?
- Yes. Warehouses need new sources, models drift as the business changes, and dashboards accumulate requests. Most clients keep one or two analytics engineers via staff augmentation from $4,500/month per engineer, while data-heavy organisations run a dedicated analytics team from $13,500/month covering data engineering, modelling, and dashboard development together.