Exploratory Data Analysis Exploratory Data Analysis (EDA) is an approach to analyzing data that focuses on gaining an understanding of the data and identifying pattern

Exploratory Data Analysis Exploratory Data Analysis (EDA) is an approach to analyzing data that focuses on gaining an understanding of the data and identifying patterns and relationships that may be present. EDA involves using visualizations and statistical techniques to explore and summarize the data in a way that is both comprehensive and intuitive. The primary goal of EDA is to uncover interesting and relevant insights that can be used to guide further analysis or inform decision-making. By examining the data from different angles and perspectives, EDA can reveal relationships and trends that may not be immediately apparent from a simple examination of the raw data. Overall, EDA is an important step in the data analysis process because it helps to identify potential relationships and patterns in the data, which can guide further analysis or inform decision-making. EDA is also an iterative process, where the insights gained from initial analysis may lead to further exploration and refinement of the analysis techniques used. Before you begin, be sure you review the following resources: https://youtu.be/5rLiz32unmg Instructions You have been asked to determine what drives conversion and revenue. Before starting, you need to understand your customer and their online behavior. This will enable the Sales, Customer Service, Marketing, and IT divisions to optimize website experiences and increase company revenues. Your marketing director sent an email asking you to analyze the online data from financial services: Good afternoon, I am sending you 52,446 records from February to June. The data consists of online activities for our financial services clients. The data represents credit cards that users have applied and where the customer originated. Please help me understand the origin of our customers. How are the customer’s finding our site? Marketing, Sales, and IT need this information to personalize the online experience for each customer. Thank you, Tom Smith Marketing Director Please review the data that you have been sent in the Financial Services.xls Download Financial Services.xls. https://ecpi.instructure.com/courses/148421/files/35815508?wrap=1 The data contains information such as how the customer came to the website, engagement with the website, and conversion information, and it can be used to optimize the end-user experience that drives revenue. After reviewing the data, answer the following questions: Assess the importance data analysis when looking at where your customers are coming from. How many customers came from Organic (found in the traffic_source column)? Why is it important to understand which customers are finding your organically? Further examine Organic sourced customers, by looking at the traffic_channel, how many organic channels are there? Which traffic channels would you focus on for your response to the email? Defend your answer. https://ecpi.instructure.com/courses/148421/modules/items/17408506 Chapter 3: Exploratory Data Analysis Using Cognitive Analytics Chapter 4: Data Visualization https://ecpi.instructure.com/courses/148421/files/35815510/download?wrap=1 https://ecpi.instructure.com/courses/148421/files/35815515/download?wrap=1