When I worked as a financial reporter for a life insurance company, I often used exploratory data analysis and visualization to track claims payouts and identify patterns in these numbers. The spreadsheets I used contained thousands of data points–—everything from the amount paid to the policyholder’s age, location, and lifestyle.
At a glance, all of this data was incredibly intimidating. Our brains simply can’t process this much information without the help of visualization tools. They let you glean vital information from mountains of data. Regardless of your industry, when you choose the right visualization method, you’ll gain valuable insight into the issues that impact your company and can make the most out of every bit of information you gather.
The Relationship Between Exploratory Data Analysis and Visualization
Exploratory data analysis is the process of gathering information without making any assumptions about what you might find. In this sense, it’s the most accurate type of data analysis. Researcher bias doesn’t skew the results of the data, and you can let the facts speak for themselves.
Visualization is the use of specialized tools to help you make sense of exploratory data. Tools like scatter plots, heat maps, and histograms display the data set in a way that anyone can readily understand. You can also switch between different types of visualization tools to identify patterns. For example, an insurance reporter might use a scatter plot to see whether there’s a correlation between the claim payout amount and the policyholder’s age. You can then switch to a histogram view for the same data set, which will help you see what the lowest and highest claim payouts are in each age group.
Exploratory data analysis and advanced visualization tools help you tell a story through data. When you use the best analytics tools, you’ll ensure that your staff and shareholders connect with the data and appreciate its impact.
The Best Exploratory Data Analysis Visualization Tools
Because the data you’re gathering is exploratory, the visualization tools you use should also be experimental in nature. You have to look at the data from multiple angles. But which tools offer you the greatest flexibility?
To choose the right exploratory data analysis (EDA) and visualization tools for your needs, first, consider what types of charts you want to create. I recommend beginning with a histogram and a scatter plot. Although these two charts analyze similar data (they both compare two sets of data to find correlations), using both may enhance your understanding of the data. A scatter plot shows you whether a correlation is present at all, while a histogram shows you how frequently this correlation appears.
To deepen your understanding of the data, you can also use:
- Heat maps to find patterns in populations or locations;
- Dot distribution maps to analyze how frequently the data points appear in specific locations;
- Pie charts and polar area diagrams to analyze proportions;
- Dendrograms (tree diagrams) to sort your data hierarchically;
- Ring charts that combine your dendrogram and pie chart findings;
- Alluvial diagrams to track changes over time; and
- Custom matrix charts that track multiple types of data in one document or dashboard.
With so many different types of charts to choose from, the exploratory data analysis and visualization process can be very complicated and time-consuming. It can take hours just to create a simple scatter plot by-hand. This is why you should use an EDA system that automatically generates these charts for you.
Choosing the Right Visualization Method for Your Needs
Every company is different—there is no one-size-fits-all data visualization solution. A data analytics firm will help you identify the most effective charts for your unique data sets and create a custom EDA system from scratch. You won’t have to sort the data on your own or waste time generating dozens of exploratory reports. Instead, you can focus on taking immediate action in response to these reports.
For example, when we worked with a successful life insurance and annuity carrier, we focused on fraud detection and prevention. Our exploratory data analysis and visualization process involved gathering detailed information about the company’s insurance agents and customers. We then fed this data into advanced algorithms, which ranked each agent and customer according to risk.
Using these visualization tools, the insurance company could identify which agents were most susceptible to getting fooled by fraudulent claims and which customers were most likely to commit fraud. As a result, fraud detection experts were able to identify fraudulent cases three times more effectively than they could before this process began. The key to selecting the best exploratory data analysis and visualization method is to hire a firm that can come up with a customized plan tailored specifically for your company. Firms like Tek Leaders have both the time and resources required to gather detailed data, clean it up, and present it in a visually-engaging and easily-accessible way. With an experienced data analytics team at your side, you can enrich your understanding of the issues that impact your company and find the perfect solutions.
To create detailed, clear visualizations to go along with your exploratory data analysis, contact Tek Leaders today. Our firm is comprised of seasoned IT experts who understand how to display complex data so that it can be readily understood by everyone who reads it. Or, if you have more questions about our data visualization services, you can reach us by email or call us at (214) 504-1600 directly.