Data Talks Core
Exploratory Data Analysis & Insights
As part of our product offering, we have the possibility to add a very important feature that will assist our customers’ decision-making process and answer important business questions. We call this feature Ad-hoc Analysis and a component of that feature is Exploratory Data Analysis & Insights.
Exploratory Data Analysis (EDA) is the process of analyzing and visualizing data to extract insights from it. Important characteristics of the data are revealed and the customer gets a better understanding of their data.
Exploratory Data Analysis & Insights is about:
• Increasing insight into a dataset
• Uncovering the underlying data structure
• Extracting important variables
• Detecting anomalies in data
• Testing assumptions
This is the process we are following:
1. Exploration of data. Looking for relationships between the data points. Exploring anomalies like duplicates, incorrect data types, missing data (nulls or empty strings) and any kind of suspicious observations. The results are communicated back to our customers to make sure that the data is correct and that no bugs are causing the outliers.
2. Analyzing using statistical models. Employing statistical models and algorithms to analyze your data and get full insights.
3. Data storytelling. Presenting the findings back to the customer in a way of data storytelling, as well as having discussions with customers to answer business questions or find new data points to look closer at.