Lesson 1Data validation rules: duplicates, referential integrity (customers/products), out-of-range values, negative prices/quantitiesSet strong validation rules to keep sales CSVs reliable. You will find duplicates, ensure links between customers and products, and mark values outside normal ranges or negative ones before they affect dashboards and further analyses.
Finding duplicate orders and linesChecking links for customers and productsValidating number ranges and limitsManaging negative prices and amountsCreating reusable validation listsLesson 2Understanding column semantics: order_id, order_date, customer_id, customer_region, product_id, product_category, product_subcategory, quantity, unit_price, discount, revenue, cost, channelMake clear the meaning and use of main sales columns in dashboards. You will connect identifiers, dates, product details, amounts, and money fields, ensuring steady meanings across models and charts for Eritrean markets.
Order identifiers and detail level choiceCustomer and area identification fieldsProduct, category, and sub-category rolesQuantity, unit price, discount, and revenueCost, channel, and margin fieldsLesson 3Handling discounts and price calculations: recomputing revenue from unit_price, quantity, and discount and reconciling with reported revenueLearn to recalculate and check revenue and price measures. You will figure line revenue from unit price, quantity, and discount, match with reported totals, and note mismatches for review in local sales data.
Revenue formulas from unit price and quantityApplying percentage and fixed discountsMatching calculated and reported revenueFinding uneven discount patternsRecording pricing and discount rulesLesson 4Time-based transformations: extracting year, quarter, month, week, weekday, rolling windows, and fiscal calendarsLearn to change order dates into useful time features for study. You will get calendar and fiscal details, make rolling windows, and ready steady time fields for dashboards and time-series models in Eritrean calendars.
Getting year, quarter, month, and weekMaking weekday and weekend signsBuilding rolling and moving window measuresSetting fiscal calendars and shiftsMatching time levels for dashboardsLesson 5Data cleaning transformations: trimming, case normalization, standardizing region and channel labelsLook at useful cleaning steps to make raw sales CSVs steady and ready for analysis. You will remove extra spaces, steady case, and standard area and channel labels to stop duplicates and broken dashboard filters.
Removing spaces and hidden charactersCase steadying for text measuresStandardizing area and channel groupsCombining near-same label typesRecording cleaning rules for reuseLesson 6Derived metrics and transformations: profit = revenue - cost, profit_margin = profit / revenue, gross_margin, AOV = revenue / order_count, unit_total = quantity * unit_priceLearn to get key sales measures from raw CSV fields. You will calculate profit, margins, AOV, and unit totals, making sure formulas are steady, well-noted, and matched with business meanings in Eritrean trade.
Calculating profit and gross marginSafely calculating profit marginGetting AOV from revenue and ordersUnit totals from quantity and unit priceMatching measures with business meaningsLesson 7Techniques for reproducible ETL: documented steps, scripts, notebooks, and checksums for CSV import integrityLearn to make repeatable ETL pipelines for sales CSVs. You will write transformations, track versions, use notebooks for study, and use checksums and checks to ensure import quality over time in local systems.
Writing repeatable CSV changesUsing notebooks for study ETLVersioning ETL code and setupChecksums and file quality checksAutomated ETL runs and recordsLesson 8Missing values and null patterns: detection methods, imputation strategies, and when to drop rowsMaster ways to find and handle missing or null values in sales CSVs. You will study null patterns, pick filling strategies, decide when to remove rows, and note assumptions to protect further measures.
Studying missingness in key columnsShowing null patterns and linksFilling strategies for number fieldsFilling strategies for category fieldsRules for safely dropping rows or columnsLesson 9Data types and parsing: date formats, numeric types, categorical encoding, handling string vs numeric valuesLearn to properly read dates, numbers, and categories in sales CSVs. You will tell text from number fields, use area-aware reading, and make strong category encodings that stay steady across updates.
Finding column data types in CSV importsReading dates with various area formatsHandling number separators and money signsMaking steady category encodingsSafely changing mixed-type columnsLesson 10Dealing with multi-line orders and aggregation at order vs order-line levelLearn to handle orders that cover multiple lines in sales CSVs. You will tell order and order-line levels, add up correctly, and avoid double counting revenue, quantity, and discounts in dashboards.
Telling order vs order-line levelAdding revenue at order levelSumming discounts across linesAvoiding double counting in totalsChoosing level for dashboard measures
