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In our previous article, we discussed the benefits of using the Microsoft recommended Centre of Excellence within your Data Landscape, but what does that look like for the typical Excel Guru in teams?

Let us use the legacy position to understand the reasoning behind the solution again. A Legacy Enterprise Analytics landscape is traditionally managed either by a specific IT team or an Application Support team. Their primary role is to ensure that the defined reports execute rather than support additional or ad-hoc analysis/reporting. This is often accomplished by supporting CSV or Excel-based downloads. This meant that changes to the “official” reports had to go through a process of change – note this is not inherently bad. This process could be akin to opening a box with the crowbar that is inside it. So you as the Excel Guru, would don your cape and use the extracts to build any reports your managers needed. Over time you stopped even asking the Platform Team for work, often because you were already so busy working on maintaining all the custom reports that were now part of your job. All while that Platform Team get all the praise! This is the backdrop that drives Modern Analytics Solutions and is why we must ensure that we do not bring the behaviours of the past with us.

As an Excel Guru, you may already be able to produce reports at least as good as anyone in Power BI, or you may not feel that pretty pictures (charts) are worth anything. Regardless the position is not uncommon, “I am used to Excel and able to accomplish everything my team and I require in it why should I give that up to support a team who don’t know what I need or do and who frankly have never been able to properly meet our needs!” – too close to the truth? The successful implementation of a Centre of Excellence requires embracing negativity and providing avenues of communication to allow you to become a subject matter expert rather than an Excel Guru. What is the difference? Simply a Subject Matter Expert (SME) is part of the Centre of Excellence while an Excel Guru by definition works in isolation to deliver value at a point. Transitioning you into being an SME must be the goal of your business if they desire success. Power BI transitions you from taking data extracts and building reports, to connecting directly to the data model and building reporting content against it. That content can include logic changes, meaning the “requirement” to export data and create it from scratch. This makes it possible for the ad-hoc updates to be fed back into the main model, so the legacy position that would mean you ended up having to constantly maintain the point solution you built, instead because the point solution was always part of the main solution it is automatically maintainted, any logic changes (new Measures) can also be fed back into the main model either as true new or if the requirement is clear overwritten. The impact of this must be seen to be believed. The cycle below shows a typical refresh cycle although, on day one of a new platform, it is not uncommon for this cycle to be executed weekly (or even daily); however as the “value” of the model increases, the frequency of the refresh decreases, to monthly, quarterly or longer.

A significant reason for the slowdown is that a well-developed large data model can produce a significant percentage of most requests immediately. Remember, most reporting/data requests are initially “I wonder what…” in nature, which is then used to finish defining the business change or challenge needed. So when you can use the primary model to answer 60 – 80% of the request as soon as it is made, that is typically acceptable, with an analogue that works being preferred to “exactly what was asked but in a week/month”.

In a past life, Ross was able to use existing IT infrastructure data to track the global staffing position of a business to track the progress of a pandemic while on a call with the CIO. The data was there, and while it was not a headcount of each site, the number of OS licences correlated well enough to headcount give a new immediate answer, over the next 24 hours, the public pandemic tracking data was added into the model to see the pandemic progress against headcount.

Your Excel knowledge is transferable into Power BI. For an Advanced Excel user, DAX —the language of analysis in Power BI — is frustrating to learn, but the basics can be rapidly understood. Connecting existing models to Excel means that if something really cannot be done by you, solve it within Excel, and a more DAX-focused colleague can fold it into the Power BI solution.

It is important that you recognise that the skills you need the most are the skills you have. The step change that a Modern Analytics Platform brings is that people without specific application skills can still deliver massive value. Remember, Power BI at this point is predominantly drag-and-drop, and the odd additional measure that is needed can be written by Copilot.

Geordie Consulting uses the Microsoft Power Platform to provide businesses with agile, cost-effective data solutions. We specialise in integrating data from across business applications into a single, manageable platform. Our services include enabling business users to develop custom reports using Power BI and Excel, leveraging Semantic Models for consistent data analysis, and enhancing user self-sufficiency through Copilot. We aim to ensure your data agility to support a data-driven business. We provide comprehensive documentation and support to maximise the business value provided by your data. Let our insight unlock your insights.