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In our previous weeks, both on LinkedIn and on our sister YouTube channel, we discussed the importance of understanding what is happening in the Modern Data Landscape you want within your organisation.

Let us start by looking at what it is you do not want, mainly because when you consider the wrong, the right makes sense. The historical position and what we now must do as much as possible to prevent is having a high-cost data solution that only provides part of the data used for board room reports. It is essential to understand how we get to that point. The crux of this issue is a lack of solution agility. This can either be programmatic or a result of process or policy challenges. Typically, in our experience and from looking at the Gartner Analytics press over the last decade and a half, this results from a combination of factors. Firstly, we must understand that at this point, blame is not of value here; really, it is about how we can ensure that your organisation moves forward appropriately.

In the early 2000s, it was widely accepted that the high skill levels required, along with the need for multiple systems and business users seeking changes, led to the necessity of gatekeeping and budgeting for what was deemed simple. Consequently, businesses began to extract data into Excel, creating their own parallel reporting systems. As time progressed, the expensive reporting solutions that had been implemented remained in place, but the core content was largely ignored. Instead, the ad-hoc reporting tools developed by the business became the preferred choice for reporting.

This shift often occurred with little to no documentation or standardization. As a result, a modern data platform must be agile and incorporate inherent feedback functionality. This means that when data needs to be brought into Excel for a specific task, the business actively seeks to integrate that work back into the enterprise platform. The concept is straightforward: develop a data platform that can be directly integrated with all your line-of-business applications. This single platform should allow business users to create limited solutions based on managed models.

So, how do we consistently deliver this for our clients?

Firstly, we recommend the Microsoft Power Platform as the platform of choice for this. In all honesty, you will find that there are better dedicated solutions that do elements, but the Power Platform is a complete solution. Fabric brings the components that Enterprise customers need to leverage within the Azure package under the same platform, further consolidating the platform’s capabilities.

Secondly, the revolutionary component of the Power Platform is the ability of both Excel and Power BI Desktop (and now the directly in the service), to connect to a published Semantic Model to build your own report.  Do not underestimate the power of this. Ross remembers having a conversation with a Microsoft Enterprise Architect and complaining that a major issue he had with the platform was that the model had to be duplicated with each and every report (this was back in early 2017); there was a knowing “huh, interesting”, then a couple of weeks later an in April 2017, Microsoft enabled this Direct Query capability to either Power BI Semantic Models (Datasets) or AAS Models. Suddenly, the platform became a true powerhouse. The biggest benefits currently come from connecting to the model using Power BI Desktop, but for all those trying to limit the amount of exporting to Excel that people do, this changes everything; export to Excel is typically then used to produce PivotTables, Direct Query connection allows you to create PivotTable.

Combining the platform’s capability to draw data sources from across your business into a single source with the end-user connectivity options makes for a robust and well-rounded solution. If we add the final cherry and tell you that when connecting to a Semantic Model from Power BI desktop, you can still create new measures (in fact, as a matter of policy, we add a “Secondary Measures” folder to all our Semantic Models and train Super User communities and developers to use it when specific additional measures are needed for a report. These can then be submitted for inclusion in the main Semantic Model at the next update cycle. The result is that in a bedded-in solution, the business value of the Semantic Model increases rather than decreases in the legacy models. Copilot is also now also making it easier for business users to be able to write their own Dax Measures, so making them more self-sufficient than ever before, but all while using the standard Semantic Model, and with the easy capability that their work can be made available to all though a simple copy and paste update.

Using the Microsoft Power Platform, Geordie Consulting provides 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.