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    Financial Data Analysis & Business Analysis with SQL

    Posted By: lucky_aut
    Financial Data Analysis & Business Analysis with SQL

    Financial Data Analysis & Business Analysis with SQL
    Published 12/2024
    MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz, 2 Ch
    Level: Intermediate | Genre: eLearning | Language: English | Duration: 21 Lectures ( 2h 7m ) | Size: 656 MB

    Financial data analysis, customer segmentation analysis, financial growth projection, budgeting with SQL

    What you'll learn
    Learn the basic fundamentals of Structured Query Language, SQL use cases, SQL core functions, and relational database management system
    Learn about basic SQL queries like select statement, order by clause, where clause, insert, update, delete, group by clause, and aggregate functions
    Learn how to do customer segmentation analysis
    Learn how to do profit margin analysis for each product
    Learn how to analyse total sales revenue by country
    Learn how to analyse total sales revenue by product
    Learn how to analyse discount impact on sales revenue and profitability
    Learn how to simulate budget allocation for manufacturing
    Learn how to analyse monthly sales performance
    Learn how to identify products with high COGS and low profit
    Learn how to do financial growth projection and forecast sales using historical data
    Learn how to clean by removing missing values and duplicates
    Learn how to reformat data using SQL
    Learn how to generate SQL queries using AI

    Requirements
    No previous experience in SQL is required
    Basic knowledge in statistics

    Description
    Welcome to Financial Data Analysis & Business Analysis with SQL course. This is a comprehensive data analysis course where you will learn step by step on how to perform financial analysis, customer segmentation analysis, profitability analysis, budget allocation, and financial growth projection using SQL. This course is a perfect combination between finance and data analytics, making it an ideal opportunity to practice your SQL skills while improving your technical knowledge. In the introduction session, you will learn the basics fundamentals of structured query language, such as getting to know its core functions, use cases, and several examples of relational database management systems. Then, in the next section, you will learn basic SQL queries like select, insert, update, and delete, which are essential for interacting with the database. You will also learn how to filter, sort, and aggregate data, allowing you to extract meaningful insights from financial data. Before starting the project, we will set up the SQLite Online which is the IDE that we will use, in addition, we will also find and download the financial dataset from Kaggle. Once everything is all set, we will begin cleaning the data by handling missing values and converting data types as needed, the objective is to ensure that the dataset is ready for analysis. Afterward, we will conduct more detailed analyses, such as examining sales revenue by country to identify the most profitable markets and exploring sales revenue by product to understand which items contribute the most to total revenue. We will also analyze the impact of discounts on overall sales to determine the effectiveness of different pricing strategies. Following these initial analyses, we will delve into more advanced topics, including budget allocation to optimize expenditure, expense tracking to monitor spending patterns, profitability analysis by product to identify high-performing products, customer segmentation analysis to understand buying behavior, and financial growth projections to forecast future financial performance. This project will enable you to build a comprehensive understanding of financial analysis and budgeting. Last but not least, at the end of the course, we will use an AI text to SQL generator to automatically translate business questions into SQL queries, streamlining the analysis process and enhancing your ability to extract insights quickly and efficiently.First of all, before getting into the course, we need to ask ourselves this question, why should we learn about SQL, why should we analyze financial data using SQL? Well, here is my answer, SQL is essential because it allows us to efficiently retrieve, analyze, and organize large datasets, providing a solid foundation for data-driven decision-making. By analyzing financial data with SQL, you can identify trends, track key metrics, and make informed decisions that drive business growth and profitability. Mastering SQL will help you transform complex financial data into actionable insights that improve budgeting, forecasting, and overall financial strategy. Additionally, SQL is often preferred over Python or R for data analysis because it is specifically designed for querying and managing large datasets directly within databases, making it faster and more efficient for handling structured financial data.Below are things that you can expect to learn from this course:Learn the basic fundamentals of Structured Query Language, SQL use cases, SQL core functions, and relational database management systemLearn how to clean data by removing missing values and duplicatesLearn how to reformat data using SQLLearn about basic SQL queries like select statement, order by clause, where clause, insert, update, delete, group by clause, and aggregate functionsLearn how to analyse total sales revenue by country using SQLLearn how to analyse total sales revenue by product using SQLLearn how to do profit margin analysis for each product with SQLLearn how to analyse discount impact on sales revenue and profitability with SQLLearn how to simulate budget allocation for manufacturing using SQLLearn how to do customer segmentation analysis with SQLLearn how to analyse monthly sales performance with SQLLearn how to identify products with high COGS and low profit with SQLLearn how to do financial growth projection and forecast sales using historical dataLearn how to generate SQL queries using AI

    Who this course is for
    Data analysts who are interested in analysing large data using SQL
    Financial analysts who are interested in utilising SQL for budgeting and modelling