Power BI Implementation End-to-end consulting and implementation

I implement an analytics database and management dashboard in Microsoft Power BI - data visualization for decisions

Every department has its own Excel. ERP says something different from GA4. Management asks for KPIs - the answer takes three days and five spreadsheet versions. Power BI only makes sense on an organized data model - not dozens of direct connections to sources. I centralize data, build a management cockpit, anomaly alerts and controlling support. One consistent source of truth for management.

Book a consultation Data Governance guide

Does this sound familiar?

Monthly report = a week in Excel

Manual exports from ERP, CRM and GA4 - the same process every month, zero automation.

ERP, marketing and finance - different numbers

No shared KPI definitions. Management doesn't know which report to trust.

Power BI “exists" but nobody uses it

Slow reports, chaotic model, no training - dashboard exists only on the demo slide.

Direct connections to 15 sources

Every report connects differently - a CRM change breaks five dashboards at once.

Problems surface too late

Margin or conversion drops visible only after month close - no alerts or trend monitoring.

No data access control

Everyone sees everything or nobody has access - no RLS and security policies.

How implementation works - 4 steps

  1. 01

    Discovery and KPI map

    Data sources (ERP, CRM, GA4, BigQuery, Sheets), report audiences, KPI definitions and business priorities.

    Deliverable: source map + KPI catalog
  2. 02

    Data architecture and ETL

    Centralized database (BigQuery / Cloud SQL / Azure), sync, Power BI semantic model, data quality.

    Deliverable: data pipeline + semantic model
  3. 03

    Cockpit and Power BI reports

    Management and operational dashboards, DAX, filters, drill-down, RLS, consistency tests vs source systems.

    Deliverable: management cockpit + operational reports
  4. 04

    Alerts, go-live and training

    Alert mechanisms (anomalies, KPI thresholds), documentation, team training and maintenance plan.

    Deliverable: alerts + documentation + training

Offer - what you get

Database and synchronization

Centralized database (BigQuery, Cloud SQL, Azure) with internal and external system data and ETL pipeline.

BigQuery ETL Azure

Power BI semantic model

Relationships, DAX measures, hierarchies, shared KPI definitions - one model instead of hundreds of raw-data reports.

DAX Model KPI

Management cockpit

Management reports: filtering, drill-down, data quality checks, key indicators on the first screen.

Cockpit Drill-down Management

Alerts and controlling

Anomaly warnings: conversion drops, budget deviations, inventory changes, trends requiring action.

Alerts Anomalies Controlling

Source integrations

ERP, CRM, GA4, BigQuery, Google Ads, spreadsheets - data in one place, not fifteen CSV exports.

ERP CRM GA4

Documentation and training

Measure descriptions, usage guide, RLS, maintenance procedures - your team knows how to use and evolve reports.

RLS Documentation Training
  • Who it's for: companies with multiple source systems (ERP, CRM, web analytics) that want one verified management cockpit - mid-size and larger organizations, controlling, management.
  • Model: implementation project (6-12 weeks depending on sources and reports); optional analytics retainer for maintenance, model growth and new KPIs. Lighter reports? See Looker Studio.
  • Outcome: tool for management and controlling decisions, faster access to information, less manual reporting and one source of truth.

Without governance frameworks a Power BI warehouse quickly becomes another data swamp. Before building the cockpit, align KPI definitions and report lineage - see Data Governance in marketing analytics in the guide for a practical starting point.

Free tools - start on your own

Before booking a consultation, assess your data maturity or estimate data layer costs for Power BI.

Data Governance Guide

How to organize data before BI - roles, policies, quality and metric consistency across systems.

Read guide

Data Governance Checklist

Quick 5-minute assessment - is your organization ready for a shared management cockpit.

Run checklist

GA4 BigQuery Calculator

Estimate data layer costs - BigQuery often sits under the Power BI model in Google/Microsoft stacks.

Calculate costs
Krzysztof Surowiecki

Krzysztof Surowiecki. I implement Power BI where a company needs one management cockpit - not another Excel file sent every Monday. I connect ERP, CRM, GA4, BigQuery and spreadsheet data into a model management understands and controlling can verify.

  • From data source map to dashboard: architecture, ETL, Power BI model, reports and alerts.
  • Experience with GA4, BigQuery and Looker Studio - I know when Power BI makes sense and when a lighter report is enough.
  • Data governance in practice: KPI definitions, access roles (RLS), documentation - not an IT “black box".

Trust - why clients trust me with Power BI

20+years of experience
150+projects
50+clients
7expert tools
  • Cockpit for decisions: KPIs visible from the first screen - filters, drill-down and alerts where needed.
  • Data consistency: one semantic model instead of dozens of reports on raw connections.
  • Knowledge transfer: team training and maintenance documentation - the report works after go-live, not just on demo.

Contact - let's take the first step

Tell me about data sources, KPIs and who will use the cockpit. In a consultation I'll propose architecture, Power BI scope and timeline.

  • Discussion of source systems (ERP, CRM, GA4, BigQuery) and reporting goals.
  • Initial management cockpit, data model and KPI priority proposal.
  • Cost, timeline and post go-live maintenance model.
Book a consultation Try DG checklist first