You may have noticed recently that Microsoft and particularly the Education team have been making quite a fuss of Power BI. (Business intelligence) If you missed it, Power BI for Office 365 is a cloud based feature which allows those who are required to manipulate or equate data, in visually stunning ways. If you missed some of our blogs, I encourage you to have a read through Power BI for Office 365 Education: Unlock the data within your institution or Power BI for Education - What’s in it and what can it do for me. Our intern also put together a compelling, student perspective - step by step guide, running through some of the top features, particularly useful for Higher Education Students - Power BI for Students.

Whether you are an educator that fall's under the Schools, Further Education or Higher Education space, I'm sure you'll agree that digital competency, surrounding the formation of data and how it’s managed is an ability, highly relevant to students, educators and many professionals across all industry sectors. Making it a somewhat unavoidable digital skill. When I left school, I certainly didn't have the data skillset that would have allowed me to be 'career ready' and almost all of the practical, business day to day skills were learned either on the job or through self-learning at home. Particularly in a previous role - I spent many hours each week compiling complex sales reports and manipulating pages and pages of Excel data sheets into various demographics before having to display this in clear week by week formats. Even with the most concise and intelligent Excel formulas to shortcut the workload - this took hours from my day and was a concentration heavy task.

For me, Excel had cropped up in numerous school lessons across the breadth of my curriculum, but the extent to which I used data when I left school, left me unprepared. Power BI in Education, offers significant learning potential around the uses of data once it's formatted into the simplest of Excel Workbooks. Not dissimilar to a mathematical equation, by subtracting 'the actual data' you are left with a series of information, that may provide critical business insight - but not if you don't know what to do with it.

After reading a number of tech blogs and watching interesting demo videos around Power BI features, one of my favourite has to be Power BI Q&A. Rather than discussing it's specification, I'd like to instead run through a learning scenario, which I feel this would be highly useful to both educators and students.

I'll start within a KS2/KS3 class. In this BYOD environment, the students in the class each have their own laptops - A range of Windows 8 devices (naturally in my scenario) via miracast the teacher presents the students with a worksheet full of data. The data represents ticket sales for a pop concert at a large music arena. The data consists of various types of ticket sales - Adults (Over 18) / Children under 12 / Young Adults between the ages of 13 - 18. The columns in the registration forms had collected a range of personalised information such as: Name, Address, Billing Address, Country, Ticket Type, Ticket Sale Price and the format in which they paid i.e Card Payment/Bank Transfer.

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After scrolling through the data and discussing what information was in front of them and what potential uses the data could have for the event organisers the teacher began instructing the class of a typical business type scenario. The event organisers had 5,000 seats to fill in the arena, they had so many reserved for children under 12 who needed to be accompanied by an adult, so many for teenagers and so on. The event's organisers wanted to work out how many seats for the concert they had sold and to which demographics to find out how many seats they had left to sell.

Once Synchronising the data via Power BI in Office 365, the teacher asked the children what they thought they needed to find out from the data and the type of questions that needed to be asked. The students were then able to use the search style Q&A tool to literally search Power BI for their response. Inspired by Bing and with a familiar format of popular search engines, the students were able to directly type in basic questions, in natural everyday language to generate responses. The style of language would equate to that which would be used between student peers or between student and teacher.

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The system is then able to translate that to add data complicity to the request. The search bar, similar to Bing, also offers alternative suggestions - giving students the opportunity to amend the question mid-way through and watch the data visualisations amend in real time. For students unsure of how to begin, automatic suggested questions are offered underneath the presented data, students can then add questions and save them into the system for future reference or projects.

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Once the students have collated and discussed all of the questions they need to ask in order to generate the results they require, they produce a highly visual report with a range of graphs and charts, including geospatial data of ticket sales with the power map feature.

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As you can see this really is a quick and simple method of understanding the process behind the collection of data and what that data can then be used for. Particularly in a professional environment. This is a simple learning scenario using just one great feature of Power BI, but there are many more and class projects can be made as complex as you like, depending on the development stage of the students.

By promoting BI in this context we are by no means lessening the need to learn real Excel formulae and have working knowledge of its functionality - however for young students learning about data, teachers wanting to use stimulating visual tools to teach or HE and FE students wanting something quick and effective to display and report important data with rich features, we really couldn't recommend Power BI enough within an educational setting.

Students are empowered to think beyond the initial complexity of the task in hand, and concentrate on the Intellect that comes after the data is processed.