Many mining companies still rely heavily on Excel spreadsheets to manage everything from financials to production and maintenance data. While digital transformation has led many to switch to SAAS or bespoke software solutions, the challenge of change management persists. For those still using Excel due to familiarity or suitability, this post will guide you on how to derive data-driven insights using your existing setups.

Syncing Data to the Dataverse

The first step towards leveraging your data for insightful analysis is ensuring it's stored securely and efficiently. If your data currently resides in Excel, consider migrating it to the Dataverse. This platform scales with your data needs and integrates seamlessly within the Power Platform ecosystem, offering superior data management capabilities compared to Excel.

What is the Dataverse?

The Dataverse is essentially a scalable SQL database within Microsoft's Power Platform, offering easy integration with Power Apps, Power BI, and Power Automate. It's designed to manage more complex data scenarios and scale within your Microsoft 365 environment.

Implementing Data Flows

Data Flows are powerful tools within the Power Platform that facilitate the movement and transformation of data from Excel into the Dataverse. They help in normalizing data, which minimizes duplication and simplifies further data modeling.

Building Semantic Models in Power BI.

With your data securely in the Dataverse, the next step is modeling that data in Power BI. Here, you can create complex calculations for KPIs such as MTD, YTD, and QTD figures, budget forecasts, and more. Power BI's features allow for more dynamic calculations and data structuring compared to Excel, enabling you to build a comprehensive data model for clearer understanding and scalability.

Creating Visualizations in Power BI

Once your semantic models are set up, it's time to translate them into visual insights. Power BI provides a vast array of visualization tools that require minimal configuration, allowing you to present your data in a user-friendly and impactful way.

In Practice:

To demonstrate this process, let's consider a typical architecture for capturing daily production data at a mine site:

1.Excel File: Data is manually entered daily.

2.Data Flow: Acts as an ETL tool that moves data from Excel to the Dataverse.

3.Dataverse: Stores data in a normalized relational database within the Power Platform.

4.Power BI Semantic Model: Calculates KPIs and forecasts from the Dataverse data.

5.Power BI Dashboard: Provides actionable insights through interactive visualizations.