5 CSV files containing mocked data of AtliQ Technologies used for learning purposes in the Data Analytics Bootcamp provided by Codebasics.
- fact_sales_monthly (date, product_code, customer_code, qty, net_sales_amount)
- fact_sales_monthly_with_cost (date, product_code, customer_code, qty, net_sales_amount, freight_cost, manufacturing_cost)
- dim_customer (customer_code, customer_name, market, platform, channel)
- dim_market (market, sub_zone, region)
- dim_product (product_code, product_name, division, segment, category, variant)
Objective:
To find the total sales generated by all customers in a country. The report includes filters to view total sales based on the selected region or market.
Tech Skills Learned:
- ETL
- Use of
SUM()formula - Pivot Tables
- Conditional Formatting
- Data Bars for visual representation
Analytical Skills Learned:
-
Understanding the background calculations required to answer business questions such as:
- Which country should we expand our business in?
- Which country is performing the best in terms of sales?
Dataset Used:
- fact_sales_monthly
- dim_customer
- dim_market
Objective:
To analyze the performance of each market in 2019, 2020, and 2021 and compare it against the given sales targets.
Tech Skills Learned:
- ETL
- Use of
SUMIFS() - Pivot Tables
- Conditional Formatting Rules
Analytical Skills Learned:
- Learning how to evaluate market performance by calculating yearly sales and comparing them with predefined targets.
Dataset Used:
- fact_sales_monthly
- dim_market
Objective:
To calculate and analyze key business KPIs required for a Profit & Loss (P&L) statement.
Tech Skills Learned:
- ETL
- Use of
SUM() SUMIFS()IF()IFERROR()- Creating a Date Table using DAX
- Pivot Tables
- Conditional Formatting Rules
Analytical Skills Learned:
- Understanding the key business KPIs required in a P&L report.
- Interpreting KPI values to make business decisions. For example, a higher COGS value may indicate the need to optimize operational processes to reduce costs.
Dataset Used:
- fact_sales_monthly
- fact_sales_monthly_with_cost
- dim_market
Objective:
To display the net sales generated by each customer across different markets.
Tech Skills Learned:
- ETL
- Use of
SUM() SUMIFS()- Pivot Tables
- Conditional Formatting Rules
Analytical Skills Learned:
- Identifying the best-performing customers in each market to support business decisions, such as offering discounts or special deals to strengthen customer loyalty and improve long-term sales.
Dataset Used:
- fact_sales_monthly
- dim_customer
- dim_market