Data Vizualization (1) (1)

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University Canada West *

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601

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Business

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May 14, 2024

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docx

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1 Data Visualization and story telling-Teamwork BISTA, Mamta Dua, Saloni Narvaez Fraga, Jennifer Liliana Velasquez Orjuela, Annie Carolina University of Canada West BUSI 650 Razi Bayati 09-03-2024

2 Abstract The report that we present below contains the analysis of the behavior of data provided on the sale of office supplements in 2 years in some cities in the United States, we proceeded to evaluate all the variables that can influence the good performance of this business, as well as the behavior of sales, profits and other data relevant to the commercial activity of this company.

3 Data exploration The exploration of the data set was carried out from the shared Excel that refers to the behavior of a data set from an office supply store. During the explain phase, we look at the data to understand its structure, identify some potential problems, and get a sense of the patterns and trends that are already present. We examined the structure of the data to understand the information we had available, we checked the data types in each column. We define the main variables in the data set to be: order ID, order date, product category, sales, and profit. Let's visualize distributions: to visualize the distribution of numerical variables and identify possible outliers and important patterns. Figure 1 Exploring Data to Tableau Data Cleaning

4 We treat missing values: We find and treat any missing values in the data set, either by removing corresponding rows such as years of purchase and some characters from zip codes. Fixed formatting errors: To ensure that columns containing dates, currencies, and other formatted data types are in the correct format We remove duplicates: To avoid counting the same observation twice in our analyses, we search for and remove any duplicate rows in the data set. We standardize values: To ensure consistency, we standardize values if there are values that represent the same thing, but are expressed differently. Figure 2 Data Exploration in Excel Data modeling

5 To ensure that the data was complete and accurate, we focused on establishing clear connections between the various tables during the data modeling process. Variables and relationships analyzed Sales trends by region : We can analyze how sales vary in different areas and if there is any area that has a higher number of sales. Product Performance: We can examine which products have the highest sales and profits, as well as which products have the lowest performance. Analysis of the profit margin of the products. We can divide customers into groups based on how they shop and determine how they differ in terms of sales and profits. Primary and foreign keys: Primary Key: In the Super Store data set, the primary key could be " Order ID". Each order has a unique ID associated with it that identifies it. Foreign Keys : " Order ID" could be a foreign key in other tables in additional information such as: shipping details or payment details. " Product ID" could be a foreign key if there is detailed information about the products in another table. Data Visualization Analysis Next, we will review the relationship analyzes in graphical form Using Tableu

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