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Sheaf Digital has developed a series of Power BI reports for the St Francis & St Clare Catholic Multi Academy Company (SFSCMAC) in Wolverhampton.

All 12 academies use the Arbor school management information system and the Power BI reports use data from Arbor’s Snowflake data warehouse. The way the data is organised in the data warehouse simplified the development of reports that now give the Trust a joined-up view of assessments, attendance and student demographics across all 12 academies.

Sheaf Digital recently delivered a one day intermediate level Power BI course to OSI Europe in Scunthorpe. The training was based on our Power BI Next Steps (intermediate) course and then tailored to be a better fit with the requirements of the OSI team.

Sheaf Digital recently delivered 4 days of Power BI Training to two separate groups from the business support team at Chesterfield College.

The training was based on our Get Started with Power BI course, but adapted to better meet the requirements of the Chesterfield College team. That’s our standard Power BI training approach - we talk to the client, find out more about the data they collect and then we build the training sessions around a series of bespoke training activities. Either we use dummy data or we use real client data to build functioning, useful dashboards.

These are some lessons learned and observations from the last 12 months of writing bespoke Power BI reports and delivering Power BI training to multi-academy trusts. They may help other schools and trusts that are about to start on a Power BI journey.

Most of the reports were bespoke reports that look at Key Stages 1 & 2 data - multi page reports that give the central team and staff with responsibility for school improvement a detailed overview of student performance across the trust.

The best Microsoft Power BI reports and dashboards are simple. They turn large sets of tabular data into user friendly, interactive visualisations that make it easier to spot data trends and other useful insights.

Simplicity really is the key. Just like with other kinds of software, users want an intuitive design that requires little or no effort to understand. Less is nearly always better.

Power BI calculated columns and measures can be confusing at first - they seem to do almost the same thing. In the following example we use some simple school attendance data to explain why calculated columns and measures are different and we show you which one to choose when you want to do more analysis of your data.

The goal with this report was to create something interactive (and engaging) that non-technical stakeholders could use to explore student satisfaction data. That’s important - we are not trying to develop a super flexible, complicated reporting tool, but instead we want to use interactivity to engage non-technical stakeholders with data about student satisfaction.

This simple interactive dashboard will answer that question. It uses data from the Department for Education’s longitudinal education outcomes dataset. It tracks graduates 1 year, 3 years and 5 years after graduation and includes a breakdown for broad subject area and university.

Here's how you can use the slicer visualization and a simple measure to filter time based data. The data is basic school attendance data.

There are two tables - Students and StudentAttendance. Not surprisingly, there’s a one to many relationship between them on StudentId. Every student gets two attendance marks a day, one in the morning and one in the afternoon. ‘P’ for present, ‘U’ for unauthorised absence and ‘A’ for authorised absence.

This is one way of looking at student performance in Power BI. It’s a simple report built on top of single table of data about students and how they score in assessments.

Three things about the dashboard are worth noting:

• It’s designed to answer a single question - how well are our students doing? Some thought has gone into the layout of the dashboard. The visualizations are simple and it is very easy to use.

• The data behind it is also deceptively simple - a single Excel table of dummy data.

• It uses some basic ‘Measures’ - custom fields in Power BI that you add to the visualizations in your report. The measures do some extra work with the data. They’re not complicated but they are an extra step that requires a bit more Power BI expertise.