Solution Architecture

AIMS transforms data into information to provide insight to our customers. This allows them to make decisions that improve the effectiveness and efficiency of their services and improve the outcomes. We use a number of techniques to pull information from data and answer questions that the customer may not have even known to ask.




Making sure to capture the correct data is the first step in deriving insight from it. Every company can generate a large amount of data from interactions with customers, employees, automatic systems, and anything else. Figuring out what parts of that data are important to the continued functioning of the group can be one of the most important steps. This helps to formulate some of the early questions the data owners may have about their data.


Data mining and data exploration are very important for determining what information your data contains. Using quick visualizations and tables, we can determine what kind of information the data might contain, and formulate questions we want to ask, if we have not been able to do so before. This can refine the questions that data owners may already have, or produce entirely new ones, as trends and outliers are discovered for the first time in the data.



In order to gain the most information possible from the data, enrichment is a necessary step. Enriching the data will add more meaning to the information already there. We will be able to enhance location information with geo-coding, so that the data can be placed in a map graphic. We can take reference data specific to your company and attach it to the rest of the data so that everything will link together appropriately.


We will do quality and population analytics on the enriched data to pull out the most information. Population analytics allow us to view the data aggregated to a population, and follow trends associated with that group. A population can be a group of people, or it can be any other group of elements in the data that can be grouped by multiple factors. By analyzing these groups, you can get information on commonalities or differences between groups, and get ahead of unfavorable trends to guide them to a better outcome.

Quality analytics (for healthcare) show both the quality of care a healthcare provider is giving to their patients, and the health status of a patient, indicating how at risk they are for health problem escalation. This allows anyone involved in health care to keep an eye on possible issues arising from provider quality or patient health status, and intervene to prevent more issues from occurring. This concept can be applied to any data that have quality standards, so that the data owners can see where problems may arise and take steps to prevent them.



Insight is gained from well planned, easy to read visuals for most people. Visuals put the data into a simpler, more understandable form. AIMS uses interactive visualizations to help our clients better understand their data by manipulating the charts and graphs themselves. This allows users to eliminate extraneous information to their question without needing to create an entirely new visualization for them. Interactive visualizations also allow the creator to incorporate both aggregate, population level data, and individual data on one person or record. If a visualization starts by showing the overview of a topic of interest, the user can then pick out data points of interests and change the visualization to only show those.


Dashboards are the best way to compile all the visualizations for a topic together, in order to create a story for the user to read and use to gain insight into the topic. They allow visualizations to be linked together into a larger whole, showing more views into a subject of interest than one visualization alone can. With interactive visualizations, dashboards can use the user selected data point on one visualization to change the views of the others on the dashboard, allowing more detail for that point to be given to the user.