Putting Power Platform Data to Work for Your Business
One of the hidden benefits of Power Platform adoption stems from its magnetic ability to pull in data from every corner of the enterprise (and beyond). As a Power Platform solutions provider that lives and breathes this stuff, it’s been fascinating to observe all the different types of valuable data being collected by the platform.
Despite having access to this treasure trove of information, there appears to be a widespread uncertainty or perhaps a lack of clarity among customers in terms of how to harness this data effectively. So, today, we thought we’d explore this phenomenon further and show you how you can use Microsoft Fabric to put this data to work for your business.
Tapping into the Power Platform Data Stream
As noted earlier, Power Platform solutions ingest a ton of useful data points — many of which have never before been accessible within the enterprise. Most of this data settles on Microsoft Dataverse, but more on that in a moment.
To put this concept into perspective, I’ve listed a few common data capture scenarios below. This list is by no means comprehensive, but it does show you how much useful data is there to be harnessed.
Power Apps
- Spreadsheet Replacements: These types of solutions replace Excel or Access databases where critical business data was previously maintained outside of the purview of the IT department. In many cases, there’s highly valuable data in there that may be seeing the light of day for the first time.
- Line of Business Apps: These types of apps oftentimes systemize processes that may be unique to a given department and run adjacent to key ERP or CRM systems. Whereas before, these processes might have run on pen and paper, now we’re collecting data to track process metrics, etc.
- Industry Solutions: Similar to line of business apps, these types of apps fill in industry-specific gaps in that may exist in core business systems. The data captured here makes it possible to compare performance against competitors or industry averages.
- One App Experiences: These types of apps (sometimes called “Superapps”) orchestrate transaction processing across multiple systems (e.g., SAP, Salesforce, and Workday). From a business process management perspective, these apps collect some very valuable metrics in terms of process flows, handoffs, bottlenecks, and so forth.
Power Pages
- Customer Self-Service Portals: These solutions often capture customer requests that may have been transmitted via phone or email in the past. Besides saving on keystrokes, these intake forms provide valuable insights into the end-to-end customer service process. In other words, we now have visibility of when the request was made and can track its movement across departments/systems. Even the unstructured comment data and attachment files can be mined to glean useful information about the customer service experience.
- Supplier Self-Service Portals: These solutions can help you gain deep insights into your supply chain. For example, a supplier might use a portal like this to log advanced shipping notifications (ASNs), report on the status of a service request, and so on. This information can be used to more deeply measure supplier performance and gain insights into potential resource or logistical bottlenecks.
Power Automate
- Cross-Functional Process Flows: Much like the superapps described above, these workflows capture a lot of useful metrics that can be used to measure performance, pinpoint process bottlenecks, and identify opportunities for improvement.
- Approval Workflows: These workflows can be used to pinpoint bottlenecks in approval processes and also (proactively) identify requests that may have slipped through the cracks.
- RPA Solutions: Using Power Automate Desktop, we can integrate with closed systems that we may not have been able to reach previously. For example, imagine that a warehouse has a series of proprietary measurement devices that automatically measure/weigh boxes as they move down conveyor belts. These hardware devices oftentimes run on some kind of proprietary Windows desktop software that doesn’t integrate with anything. Using RPA bots, we can gain access to this data and incorporate it into larger-scale workflows that might take those measurements and feed them into a warehouse management system (WMS) where they could be used to plan deliveries, etc.
Breaking Down Information Silos
Most of the data collected through the various solutions highlighted in the previous section ends up getting stored in Microsoft Dataverse. As we discussed in this space recently, Dataverse is way more than just a database and a perfect place for collecting both structured and unstructured data. The trick is determining the best way to unlock that data and put it to work for your business.
A quick and easy way to tap into this data is to use the Dataverse connector in Power BI to create ad hoc reports and dashboards. This approach creates a direct connection to Dataverse and accesses the data in real time (see Figure 2).
While the Power BI direct approach is quick and easy, it’s not without its limitations. As customers continue to mature on Power Platform, it’s easy to accumulate many Dataverse environments (e.g., separate environments by department, etc.). Before too long, data is broken up into silos and all those point-to-point Power BI connections become quite a chore to manage.
Speaking of information silos, another issue with the direct connection approach is that it pretty much limits you to just analyzing the data in Dataverse. While this information is useful to a point, it’s way more useful if we combine it with data across the enterprise to tell larger, more complete stories.
Building on Microsoft Fabric
At the end of the day, what we really want to do is integrate the data we’re collecting from Dataverse into the overall data landscape. Fortunately, that’s way easier to accomplish than you might think. These days, there are two code-free and easy ways to replicate Dataverse data into data warehouses:
- Azure Synapse Link for Dataverse: With Synapse Link, data can be replicated in near real-time from Dataverse into Azure Synapse Analytics (specifically Azure Data Lake Storage).
- Dataverse Shortcuts for OneLake: With this option, a “shortcut” is created in Microsoft OneLake that points to the Dataverse data. In this scenario, no data replication is necessary.
Figure 3 below illustrates what this looks like with Microsoft Fabric and OneLake. As you can see in the figure, this approach unlocks the ability to combine the data accumulated in Dataverse with other enterprise data assets including:
- SAP or Oracle ERP systems
- Salesforce or Dynamics 365 CRM systems
- SaaS solutions like Workday or Coupa
- Cloud or home-grown databases
- Semi-structured text files, images, etc.
Once we get the Dataverse data into OneLake, we can put it to work in a variety of different ways:
- Data Engineers: Data engineers can mix-and-match the Dataverse data with other data sources to curate data models that can be used to create advanced reports/dashboards, develop data science applications, and so forth.
- Data Analysts: Business and data analysts can consume the data models built by data engineers to perform self-service analytics and make informed, data-driven decisions.
- Data Scientists: Data scientists can use the data to build data science applications that utilize AI and machine learning technologies to mine for insights, analyze trends, detect anomalies, and so forth.
Closing Thoughts
From a data perspective, Power Platform is the gift that keeps on giving. In many cases, data that’s being accumulated in your Power Platform systems may be the missing link that helps you fill in the gaps with process flows so that you can accurately measure them end-to-end.
If you’re new to Microsoft Fabric, stay tuned to this space as we have more exciting content on the way. We truly believe that Fabric is going to be a game changer for businesses looking to make data-driven decisions.
