Custom Data Visualization Services

The size and use of large modern datasets are rapidly increasing in direct contradiction to the static nature of these reports. A typical data chart shows a 3-dimensional data set using a line chart. For example, modern day visualization technology provides a 5 or 6-dimensional view of a multi-dimensional data set using a motion bubble chart. This is Professor Hans Rosling’s (technology which was purchased by Google) original motion chart demo, which shows the type of work that Practical Computer Applications (PCA) produces for clients.

Data Visualization

Dashboards, data visualization, and interactive drill-down make your data more useful and actionable.

BI And Analytics

Identify hidden trends, operational and financial patterns, buying behavior, and business opportunities.

Database Consulting

Leading companies have selected us to handle entire SQL, Access, and SQL databases to assist with their information systems.

The new visual paradigm

This new visual paradigm enables users to instinctively see previously hidden stories in the data. Our clients find information faster and make better decisions. Here are some of the things that data visualization enables our clients to do:

  1. We can visually discover trends and tendencies among measures, attributes and parameters
  2. Outliers, anomalies, exceptions, and data errors will be visually presented to us
  3. We will see clusters, relationships and relative sizes in datasets
  4. We may visually analyze the composition of totals, comparison and distribution of data points
  5. We can see special, similar, or unusual data to trigger automatic or visual alerts
  6. We can find a “Needle in Haystack” by interactively drill-down to specific details

Coordinated Graphs To Spot Trends

When faced with a spreadsheet containing large amounts of data, the hardest thing is often just to find the relevant data. For example, if you had a database containing information on thousands of medical studies, how would you find just the ones you need? The spreadsheet view on the top of the example shows what you might be dealing with. If you wanted to find the reports that contained information on elderly patients with at least 100 patients, you would need to sort and filter the results.

Below the table is a graphical representation of the same data. The studies on the elderly are represented by the dark blue circles and any dark blue circle that is above the 100 line is our populations. If this was a real working program instead of an illustration, you could click on one or more circles to open the reports.

Finding Outliers And Correcting Errors

One of the unsung, but valuable, uses for data visualization is to find outliers and potential data entry errors. The graph on the left shows several unusual data points. There are a cluster of three data points on the top left of the screen that do not follow the general trend of the data and are by themselves.

If this was a real analysis, clicking on the data points would open the record behind the information so that you can see why these points are different. You may find that these data points are critical findings, such as exceptions that could cause a life threatening situation. Or, they could be the data points that unveil a new major finding that leads to success.

On the right are pie charts showing another aspect of the same data. However, looking at the legend quickly shows that there are some errors in the data. For example, “Hospital (Inpatient)” appears to have two entries. It is likely that one of the two entries contains an extra space. Here, the problem is easy to spot using a legend in a chart.

Finding The Needle

When faced with a spreadsheet containing large amounts of data, the hardest thing is often just to find the relevant data. For example, if you had a database containing information on thousands of medical studies, how would you find just the ones you need? The spreadsheet view on the top of the example shows what you might be dealing with. If you wanted to find the reports that contained information on elderly patients with at least 100 patients, you would need to sort and filter the results.

Below the table is a graphical representation of the same data. The studies on the elderly are represented by the dark blue circles and any dark blue circle that is above the 100 line is our populations. If this was a real working program instead of an illustration, you could click on one or more circles to open the reports.