Power BI vs Manufacturing Analytics
Manufacturers are looking at their data closer than ever before. The accuracy, volume, and context have never been more valuable. Data has the ability to transform the businesses of almost every discrete manufacturer. Having the right data on production processes is the most effective way to reduce downtime and increase throughput. So needless to say, manufacturers are looking for solutions that help them acquire and contextualize this data.
This means manufacturers are looking for systems that can affordably collect and analyze all of their machine data. Today, we are going to compare Microsoft Power BI vs. Manufacturing Analytics.
Are Business Intelligence and Manufacturing Analytics the Same Thing?
Many companies look at manufacturing analytics applications and believe that Power BI, or other business intelligence software such as Tableau, are nearly identical. The truth is that they are slightly different. It is true that there is some overlap between the visualization capabilities of a traditional manufacturing analytics application and classical business intelligence, but they both are suited for totally different goals.
A true manufacturing analytics application must do the following:
- Acquire Data
- Clean & Contextualize Data
- Calculate Manufacturing KPIs
- Produce Role-Based Visualizations & Dashboards
What is Mingo Smart Factory?
Mingo is an award-winning smart factory and manufacturing analytics solution. It strips out all the complexity associated with implementation times and configuration and simply integrates with all of your existing machines. It then takes data right out of these machines (or accepts manual entries) and automatically contextualizes the information into pre-configured dashboards built for thousands of different job roles and functions.
Every organization can easily customize what data each job role sees and how the data is presented. No configurations or traditional implementations. The primary goal of most manufacturers that implement these solutions is to centralize the data and provide meaningful access to all members of the organization.
Most of the time, the goal of these types of manufacturing analytics applications is to have them up and running and generating ROI in less than a month. Mingo was designed specifically for these precise projects.
Mingo Makes the Data Meaningful Right Out of the Box
Mingo cleans the data as it is collected from the equipment, all data coming from the machines may not be relevant and should not be processed. Some data should be filtered inside the plant and some once the data is sent to the cloud. This is done to reduce the noise and make sure the data used by the Manufacturing Analytics system is ready for display and calculations without further processing.
As the data is ingested, the context of what department, facility, shift, product, team, operator and production line, etc. this data is associated with, is added. Additionally, the reasons why a part was scraped or why a line was down can be added to help with analysis. Without context the data is meaningless.
What is Microsoft Power BI?
Power BI is Microsoft’s core business intelligence product inside the MS Suite. In our opinion, it is one of the best BI solutions on the market; one that is designed to work with thousands of different industries.
Power BI can be deployed in the cloud or on-premises and customers typically pay-per-user or per server license fees as well as designer licenses. If you already use the MS Suite, it can be added relatively easily.
Power BI is Powerful but Needs Your Direction
Many companies have built manufacturing dashboards using Power BI. There are hundreds of different types of plots and charts a user can build allowing them to try many different options to display data exactly the way they want it. Custom building data displays allow users to dig through the data and build their own visualizations; meaning you could build just about any of the dashboards that come pre-configured in Mingo. This can be very useful for more technically advanced users.
To actually get Power BI to provide your organization with anything meaningful, you need a technical user that knows how to connect to your data, set up the server, and configure the initial data sets. When using the cloud system with on-premises databases, data must be synchronized with the server. This means you can have a lag of up to an hour for the data to refresh.
The Trouble with Power BI
As you can see by reading above, Power BI vs manufacturing analytics has a few key differences:
- Power BI does not acquire data, it relies on existing databases. Companies must deploy data acquisition solutions in each factory and synchronize that data with Power BI.
- Power BI does not automatically clean or contextualize the data.
- All dashboards and data visualizations must be built by an advanced technical user or consultant.
These missing pieces are expensive. They also require a more technical and industry-specific understanding to configure. If these resources are available in-house, it is doable without outside consultants. However, it’s fair to mention that many of these projects spin out of control quickly when the visualizations and dashboards are not displaying meaningful information after the initial setup.
Should I Use Manufacturing Analytics or Power BI?
How do decide between Power BI vs manufacturing analytics? If you are looking for a general-purpose business intelligence tool, then Power BI could be the right tool for that job. If you want to understand your manufacturing data to improve uptime, quality, and performance of your factory then Mingo is going to be much more affordable and easy to implement. It will provide you with everything you need for data to context right out of the box. Power BI will take additional implementations, products, and possibly consultants to perform many of the same common functions manufacturers are seeking.