Visualizing complex manufacturing data with embedded analytics

July 1, 2022

Visualizations are the first step in making sense of data and translating raw numbers into meaningful information.

Infragistics’ Casey McGuigan

The burgeoning amount of data from machines, orders, delivery and people and its undisputed importance for businesses make data-visualization an essential part of a manufacturing organization’s strategy. 

Visualizations are the first step in making sense of data and translating raw numbers into meaningful information. Most people are used to working with simple data, but very often what remains untapped, and is everywhere around us is complex data. 

However, analyzing complex data is not an easy task. 

To translate and visualize complex manufacturing data in a simple, understandable way, data analysts must use different methods of data visualization like charts, graphs, plots, maps, diagrams, etc.

Choosing the right visualization type is the best and most secure way to make your data understandable. Poorly selected visualization types won’t let you leverage the full potential of your data and can even make it irrelevant. 

Let's explore what complex data is and how tools like embedded analytics can help you visualize and monetize your complex data.

What is considered complex data? 

Everything that does not fall into the traditional field structure (alpha, numeric, dates) of a relational DBMS is complex data. A complex data type is typically a composite of other data types, including time-series, maps, images and videos, word-processing documents, etc. 

What is complex data analytics?

Complex data analytics refers to the use of advanced algorithms to process and analyze large unstructured data sets and big-data structures effectively. A complex data set is usually more difficult to prepare, process and analyze than simple data, and often it will require a different and more sophisticated set of business-intelligence tools to do so. Also, complex data requires additional preparation and modeling of the data before it is ready for analysis and visualization. 

Analyzing & visualizing complex data

We use data-visualization tools and techniques in manufacturing to quickly make sense of data, which otherwise would be difficult to understand and draw conclusions from. Many data-visualization tools, however, use legacy systems, which makes it difficult to analyze and visualize complex data in real time. Other modern solutions like embedded-analytics tools help integrate and bring robust visualization tools, functionalities, and interactive dashboards directly to manufacturers so they can visualize complex data easily to allow simple understanding of complex relationships within the data. 

Many manufacturing organizations use a variety of different data sources, some of which are independent, hence making it difficult to make connections between them. Embedded analytics tools allow for an easy connection and integration of your disparate data into one unified view, which can serve as a source of new opportunities and advantages. 

Interactive dashboards, for example, can represent a complex data story in a simple and clear way so that everyone from plant managers and warehouse workers to technicians and assemblers can understand them. With interactive data-visualization and dashboards, you can also quickly identify trends and relationships between complex manufacturing data sets, with the ability to observe how they change over time. Furthermore, incorporated embedded-analytics features like chart-filtering can help users highlight and filter dashboard data to make smarter decisions faster. 

Another great functionality is predictive analytics, which helps forecast market demand. As a manufacturer, you know how unstable market demand can be and how difficult it is to forecast and address future market needs. Embedded-analytics solutions that leverage predictive-analytics functionality provide you with a clear and comprehensive view of all the manufacturing processes so you can easily identify recurring trends and anomalies in your data. Having that information makes it easier to determine what needs to be prioritized and where your operation focus should be for maximum profitability. 

By using interactive data-visualization tools to summarize complex data, decision-makers across the organization can absorb the information quickly to evaluate and interpret the data to guide their decision-making process.


Data-visualization changes the nature of how decisions are made in the manufacturing world today. Organizations’ decision-making processes have undergone a tremendous shift in the last two decades—switching their centers of gravity in the decision-making process from human expertise to facts backed by data.

As a result, data-visualization has become a valuable decision-making tool. Organizations that gather, process, analyze, and visualize complex data to promptly act on it enjoy a competitive advantage in the marketplace as they make more informed and more intelligent decisions than their competitors. 

Embedded-analytics tools add other benefits, too. By providing users with relevant, timely and understandable insights within manufacturers’ workflows, such solutions encourage more analytical thinking. When manufacturers are using an embedded-analytics tool, they are looking at data in context, which removes the need to switch between different apps. When they don’t waste time switching between different applications to find the insights they need, they can spend more time on essential tasks. Access to data is better and faster since all business information is stored in one single location. 

In-context analytics enables users to base their decisions on the information available at the moment or visible on the specific dashboards or data-visualization they are currently viewing. 

Final words... 

Not every manufacturing organization knows how to deal with complex data effectively. That’s why you need the right data-analytics and visualization tool. Your complex data can be a never-ending stream of business value if you can properly analyze and utilize it. If not, complex data becomes a burden, rather than an asset.

Connecting disparate data sources into one unified view is much easier with a manufacturing-analytics solution that can help you abstract away from complexity to present a quick and simple, high-level view to an otherwise complex data set. With an embedded analytics solution, you get more than an easy way to visualize your complex data; you will leverage a centralized view of all your data, increase operational efficiency, and increase ROI.

Casey McGuigan is Infragistics’ Slingshot and Reveal product manager