Dwight Newbold is our resident Data Scientist. He has a passion for data, statistical modeling and creating new methods of visualizing complex data. We asked Dwight to share some thoughts on why capturing rich data is important, and what organizations are missing out on when they neglect the data. Here’s what he had to say:
Data is a constant in our daily lives. Almost every aspect of our lives is somehow recorded and each record offers a glimpse into our habits and thoughts. These snippets have intangible value, and this value has resulted in a “big data” revolution over the past few years.
Organizations are realizing the importance of data-based decision-making. There exist patterns in data that are slight in nature. If these slight patterns get noticed in time, they can be exploited, result in actionable insights, split-second decision-making, and ultimately better outcomes.
Your analysis, along with your interpretation should tell a complete story. It should paint a picture of the past, present, as well as offering you a view through the looking glass of what is yet to come.
Exploratory data analysis, confirmatory data analysis, and predictive modeling are essential to the story. Statistical methods, coupled with high-quality graphical techniques, are crucial. They help us understand what is going on and lead to making intelligent decisions.
“Insight, not hindsight is the essence of predictive analytics” -Ravi Kalakota
To further Ravi’s point, I would say that being proactive, not reactive is the nature of the analytics beast nowadays.
Given the mass of data available and computing power at our disposal, gaining valuable insights is not a difficult feat. Yet, many organizations are still missing out on this opportunity.
It should be easy to use many disciplines to drive decision-making. You should have complete control of your data sets. This means the ability to collect quality data, incorporate external data sets, produce dynamic graphs and dashboards, view a snapshot of your past data, and use predictive analytics and various statistical modeling techniques to drive the decision-making.
Data analysis brings about important trends, patterns, and relationships that are essential in driving decision-making.