Power BI

Turn marketing and business data into consistent, trusted reporting in the Microsoft analytics environment your organisation already uses.

What it is

Power BI is Microsoft’s business intelligence and data visualisation platform. It connects data from marketing platforms, cloud data warehouses and wider business systems to create interactive dashboards, reports and analytics.

For marketing teams, Power BI can bring together data from sources such as Google Analytics, Google Ads, CRM systems, BigQuery and Snowflake alongside finance, sales and operational data.

At the centre of a strong Power BI environment is the semantic model. It defines relationships, business logic and shared metrics so measures such as media spend, conversions, customer acquisition cost and return on investment are calculated consistently across reports.

Rather than rebuilding those definitions for every dashboard, a governed Power BI environment creates a shared reporting layer the wider organisation can use and trust.

Why it matters

Organisations increasingly need to connect marketing performance with sales, customer, finance and operational data to understand what marketing is contributing to the wider business.

Without shared definitions and governance, different dashboards can quickly produce different answers to the same question.

Power BI provides a way to bring those sources together while maintaining consistent metrics, access controls and reporting standards.

As Microsoft Fabric expands the broader data and analytics ecosystem, getting the underlying architecture right also helps organisations scale reporting without adding unnecessary complexity.

What Louder does

Serving layer design - modelled marts in BigQuery or Snowflake built for reporting, rather than Power BI pointed at raw event tables.
Connectivity - BigQuery and Snowflake connectors, service account and gateway configuration, and credential handling that doesn’t depend on one person’s machine.
Semantic model and measure library - a single governed definition of spend, conversions, cost per acquisition and return, reused across every report.
Refresh and capacity planning - incremental refresh, schedule design and licensing that matches the freshness the business actually needs.
Report design - built around the decisions being made, with the discipline to leave out what nobody acts on.
Migration - moving from Looker Studio, spreadsheets or manual decks without losing the definitions people already trust.

Common challenges

DirectQuery pointed at raw event tables. Reports are slow, and on on-demand BigQuery billing every filter click is a billable scan.
Refresh limits discovered after the promise. Standard workspaces cap scheduled refreshes per day. Teams commit to hourly reporting and then find the licensing won’t support it.
Gateway as a single point of failure. One on-premises gateway, one machine, one credential that expires without warning, and no second person who knows how it was set up.
Row-level security retrofitted. Adding RLS to a model built without it generally means rebuilding the model, which is why it stays on the list until an access incident moves it to the top.