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Business Intelligence & Dashboards

A dashboard nobody trusts is more expensive than no dashboard at all.

We design BI solutions that people actually use. Consistent metrics, self-service access, real-time data — from executive reporting to operational dashboards.

>80%
Dashboard adoption
Minutes
Time to insight
4-8 weeks
Implementation
>60%
Self-service share

Why Most BI Projects Fail

It’s not the technology. Technology is solved — Power BI, Tableau, Looker, Grafana can handle practically anything. Projects fail because of:

1. Untrustworthy Data

Dashboard shows revenue of 12.3M, but finance says 11.8M. After two such experiences, management returns to Excel. Solution: Data platform first, quality checks and semantic layer. Only then visualization.

2. Dashboard for Nobody

IT creates 50 dashboards based on their own assumptions. Business doesn’t open them because they don’t answer their questions. Solution: Design thinking — we start with user workshops, map decisions and questions, design visualizations together.

3. No Self-Service

Every new report = IT ticket, 2-week wait. Analysts are frustrated, management impatient. Solution: Self-service layer with governance — certified datasets, documentation, training. IT builds the platform, business uses it.

Our Approach to BI

Phase 1: Discovery and Requirements (1-2 weeks)

Workshops with business stakeholders: - What decisions do you make? Based on what data? - What takes too long today? What’s missing? - Who are the consumers? Executive, manager, analyst, operator? - What’s the required latency? Real-time, daily, weekly?

Output: Prioritized list of dashboards/reports with wireframes and defined KPIs.

Phase 2: Semantic Layer and Data Model (2-3 weeks)

Before creating the first visualization, we need a reliable data foundation:

  • Semantic layer: Unified metric definitions (revenue, margin, churn, NPS…) — one calculation, one truth
  • Data model: Star/snowflake schema optimized for analytical queries
  • Dimensions and facts: Time, product, customer, region — consistent hierarchies
  • Row-level security: Who sees what — automatically by role/region/team

Phase 3: Dashboard Development (2-4 weeks)

Executive dashboards: KPIs on one page. Revenue, margin, pipeline, cash flow. Drill-down to detail. Mobile-friendly. Automatic daily email with overview.

Operational dashboards: Real-time metrics for day-to-day decision making. Orders, inventory, SLA, throughput. Alerting when thresholds are exceeded. Grafana for operations, Power BI for business.

Analytical reports: Ad-hoc exploration for analysts. Self-service access to certified datasets. Pivot tables, slice & dice, Excel export. Power BI Analyze in Excel for power users.

Phase 4: Self-Service and Adoption (ongoing)

Data catalog: Analyst searches for “customer lifetime value” → finds definition, owner, quality score, query examples. No IT ticket needed.

Training: Hands-on workshops for users. Power BI Desktop for analysts, Service for sharing, Mobile for management. Best practices, anti-patterns, governance rules.

Governance: Certified vs. exploratory datasets. Promotion workflow — analyst creates report, reviewer approves, publication for broader audience. Versioning and change management.

Technologies We Deploy

Power BI

Our primary choice for Microsoft-centric organizations. Strong semantic model (DAX), native integration with Azure and Office 365, competitive pricing. Power BI Premium for large-scale deployment, Embedded for customer portals.

Tableau

Strongest visual exploration and ad-hoc analysis. Drag-and-drop interface that analysts love. Tableau Cloud for SaaS, Tableau Server for on-premise. VizQL for intuitive data interaction.

Grafana

Open-source, ideal for operational monitoring and real-time dashboards. Native integration with Prometheus, InfluxDB, Elasticsearch. Alerting, annotations, templated dashboards. Zero license costs.

Metabase / Apache Superset

Open-source alternatives for self-service BI. Low barrier to entry, SQL-based queries, embedding-friendly. Suitable for startups and smaller teams with limited budgets.

Measurable Results

Our BI implementations typically deliver: - 80% reduction in report preparation time (from days to minutes) - Unified metrics across the entire organization — end of “our numbers vs. your numbers” - Self-service adoption >60% — analysts get data themselves - Faster decision making — data available in real-time, not with weekly delays

Časté otázky

Power BI is the better choice for companies with Microsoft stack (Azure, Office 365) — lower cost, native integration, excellent semantic model. Tableau excels in visual exploration and ad-hoc analysis. For operational dashboards, consider Grafana (open-source, real-time). We'll recommend based on your stack and use cases.

Design thinking approach: we start with users — what they need to know, when, in what context. Prototype → feedback → iteration. Embedding into existing workflows (Teams, email, mobile app). Training and change management. A dashboard that users don't open is useless.

Semantic layer — unified definition of all business metrics in one place. 'Revenue' means the same thing in every report. We implement through dbt metrics, Power BI semantic model, or Cube.js. One number, one truth.

Yes. Power BI Embedded, Tableau Embedded, or Metabase/Superset for open-source alternatives. White-label, row-level security per tenant, API for programmatic report generation.

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