Power BI

One number for each KPI, refreshed without manual reports.

We connect your ERP, CRM, spreadsheets and SharePoint into a single semantic model in Power BI, with scheduled refresh and role-based access.

Why your data still does not drive decisions

These scenarios have a solution, and it does not require expensive BI or a multi-year project.

Reports built by hand in Excel every week, a process that eats up time and breaks whenever a formula changes.

Each department has its own version of the numbers, and meetings start with a debate over which figure is right.

Decisions made with last week's numbers, because the report depends on someone consolidating the spreadsheet.

Managers who depend on IT to extract any report outside the standard.

The data lives in the ERP, the CRM and spreadsheets, but no one can cross-reference it.

KPIs defined on paper that are never tracked because there is no accessible visualization.

How Power BI solves it in practice

We integrate your data sources (SQL Server, Excel, ERP, CRM, SharePoint and APIs) into a single semantic model in Power BI. We publish the reports to the Power BI Service with scheduled refresh and row-level security (RLS), so each person sees only the data that applies to them.

We use Power Query for transformation and cleansing, DAX for business calculations and dataflows to reuse the same preparation across several reports. Every department sees the same KPI figure, in the browser or on the phone.

A manager who opens the dashboard before the meeting leaves with answers, not questions. That is the starting point for a data culture.

How we run a Power BI project

From scattered data to dashboards in production in just a few weeks.

  1. Step 01

    KPI discovery

    We identify which indicators truly support decisions, not just what is easy to show.

  2. Step 02

    Data inventory and connection

    We map the sources, document key columns and configure the connections in Power Query.

  3. Step 03

    Semantic modeling

    We build the star schema, define DAX measures and ensure consistency across reports.

  4. Step 04

    Development and validation

    Dashboards developed and validated with business users before publishing.

  5. Step 05

    Publishing and enablement

    Publishing to the Power BI Service, scheduled refresh (with an on-premises data gateway when the source runs on your own server) and training for autonomy.

What your management gains

  • The same KPI figure in every department, with no conflicting versions
  • Scheduled data refresh, with no one exporting spreadsheets
  • Access from the browser or the phone, with row-level security (RLS)
  • Meetings that start from the agreed figure, not from arguing over it
  • Trends spotted before they become problems
  • Email alerts when a KPI crosses the defined threshold
  • A Power Apps app inside the report, to approve, correct or record without leaving the dashboard
  • Paginated reports for formal exports

Technologies used

  • Power BI Desktop e Power BI Service
  • Power Query (M language)
  • DAX (Data Analysis Expressions)
  • Dataflows Gen2 (Microsoft Fabric)
  • Migration from Azure Analysis Services to Power BI
  • SQL Server / Azure SQL
  • SAP, Oracle e APIs REST
  • Microsoft 365 / SharePoint

Application examples

Illustrative scenarios to guide the assessment, not projects delivered by Yottaflow.

Retail / Store network

Unified dashboard for a network of 12 stores

Scenario

Each store emailed its sales spreadsheet. Consolidating them for the director took 3 days and arrived with typing errors.

Solution

A Power BI dashboard connected to each store's POS through the on-premises data gateway, with scheduled refreshes throughout the day, store ranking, mix analysis and stockout alerts.

Finance / Credit

Risk and default dashboard

Scenario

The default report took 2 days to consolidate, and risk analysis by segment was done by hand every week.

Solution

A data model integrated with the credit system and Excel, with a panel of arrears by days overdue, risk segmentation and the portfolio's historical evolution.

Industry / Production

OEE (overall equipment effectiveness) and production indicators by shift

Scenario

Plant efficiency indicators were calculated at the end of the shift, in a spreadsheet, with no structured history for root-cause analysis.

Solution

Data collection per production line, with an OEE dashboard, stoppages by cause and trends by shift and by operator.

What you become able to do

  • Access without waiting on IT Managers open the dashboard when they need it, with the view for their decision level. In the assessment, we size the viewer licenses (Pro, or Fabric F64 capacity for many viewers).
  • Automatic alerts When a KPI crosses the defined threshold, the Power BI data alert sends an email and, with a Power Automate flow, a Teams message as well. The check runs on every data refresh.
  • Traceability When the source keeps history, or when it is stored in a data warehouse, the model supports retroactive analysis with the same calculation rule.
  • AI integration A semantic model ready for Power BI AI features such as Copilot (requires paid Microsoft Fabric capacity) and for predictive models in Azure Machine Learning.

Why Yottaflow

Focus on decisions, not charts

We start with the KPIs that support your meetings, not with what is technically possible to show.

Solid semantic modeling

Star schemas with correct DAX, instead of quick reports that choke on volume or produce wrong numbers.

One semantic model for every department

We eliminate inconsistency across departments with a single semantic model shared by all of them.

Team enablement

We deliver with technical documentation and training so your team can build derived reports without depending on us.

What it costs: Power BI projects start with the Assessment or go straight to Implementation. See plans and price ranges

Which report does your team still build by hand every week?

Book a free discovery call. In 30 minutes we map your data sources and the highest-impact KPIs.

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