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sql-data-analysis-project

Overview

SQL scripts for data exploration, analytics, and reporting. These scripts cover various analyses such as database exploration, measures and metrics, time-based trends, cumulative analytics, segmentation.

DataStructure Overview

Data_Structure

Exploring Database Columns

Exploring_Database_Columns

Exploring Database Tables

Exploring_Database_Tables

EXPLORATORY DATA ANALYSIS(EDA)

Data starting and ending date 2010-2014 Here I am Finding EDA From the given dataset, I Analysed Five Important Exploration For Data Analysis that is: Dimension Exploration, Date Exploration, Measure Exploration, Magnitude Exploration, Rank Exploration

Dimensions Exploration

Identifying the unique values(or categories) in each dimension. This will help us to understand recognizing how data might be grouped or segmented. which is useful for later analysis. eg: DISTINCT[Dimension], DISTINCT[country], DISTINCT[category], DISTINCT[product]

Finding Youngest and Oldest Customers

Date_Exploration_youngestandoldest_customers

Distinct Countries

Dimension exploration_distinct products_01

Distinct Categories

Dimension exploration_distinct products_01

Distinct Products

Dimension exploration_distinct products_02

Date Exploration

Identify the earliest and latest dates(boundries). Understand the scope of he data and the timespan. In order to get earliest and latest date MIN / MAX functions is very useful

Finding Oldest & youngest Customers With Age

Date_Exploration_full_customer with age

Oldest Date

Date_Exploration_full_earliest_date

Latest Date

Date_Exploration_full_latest_date

Month Range

Date_Exploration_range_of_months

Year Range

Date_Exploration_range_of_years

Youngest and Oldest Birthdate

Date_Exploration_youngestandoldest_customers

Measure Exploration (Big Numbers)

Calculate the key matrics of the business(Big Numbers). -Highest level of aggregation -Lowest level if details using SUM,AVG,COUNT functions

Overall Measure Exploration

Measure_exploration

Measure Average Price

Measure_exploration_average_price

Total Number of Customers

Measure_exploration_total_customers

Total Orders

Measure_exploration_total_orders

Total Products

Measure_exploration_total_products

Total Quantity

Measure_exploration_total_qantity

Total Sales

Measure_exploration_total_sales

Magnitude

Compare the measure values by categories. It help us to understand the importance of different categories.

Total Customers by Country

magnitude_exploration_customers_by_country

Customers by Gender

magnitude_exploration_customers_by_gender

Distribution of sold items across Countries

Magnitude_sold_items_across_countries

Average Cost in each Category

Magnitude_total_average_cost_category

Total Products by Category

Magnitude_total_Products_by_category

Revenue Generated by each Category

Magnitude_total_revenue_category

Ranking (TOPN - BottomN) Analysis

Order the values of dimensions by measures. The Top N Performers and Bottom N Performers

Top Products

Rank_top_5_products

Worst Performing Products

Rank_top_Worst performing_products This are my exploration using SQL queries and i believe it will answer some important business questions Thank you!.....

🌟 About Me

Hi there! I'm Gowtham Subramanian, I’m an IT professional and passionate Data Analyst on a mission to share knowledge and make working with data enjoyable and engaging!

Let's stay in touch! Feel free to connect with me on the following platforms: LinkedIn

About

Data Analysis with SQL Server, Including results and Basic Insights.

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