Lesson 1Filtering Methods: WHERE vs HAVING, Using EXISTS, IN, Linked SubqueriesBuild sharp filtering plans for analytical queries. Compare WHERE and HAVING, apply EXISTS and IN for subquery filters, and use linked subqueries to show complex, row-specific analytical needs in Nigerian data scenarios.
WHERE vs HAVING in Grouped QueriesUsing IN and NOT IN with SubqueriesEXISTS and NOT EXISTS for Semi JoinsLinked Subqueries for Row-Specific LogicManaging NULLs in Filter ConditionsSpeed Tips for Complex FiltersLesson 2SQL Data Types and Date/Time Management (DATE, TIMESTAMP, Number Accuracy)Grasp main SQL data types for analytics and their impact on storage, accuracy, and maths. Understand number scales, text handling, and solid date and timestamp work for time analysis in Nigerian contexts.
Number Types and Accuracy for MetricsCharacter and Text Data NotesDATE vs TIMESTAMP and Time ZonesChanging and Converting TypesDate Maths and Interval CalculationsPulling Date Parts for GroupingLesson 3Summing and Grouping: GROUP BY, HAVING, COUNT, SUM, AVG, MIN, MAXLearn to sum data with groupings and aggregates. Use GROUP BY and HAVING to create metrics, apply COUNT, SUM, AVG, MIN, MAX, and build strong aggregate queries for dashboards and reports in Nigerian businesses.
GROUP BY Basics and SyntaxAggregate Functions COUNT and SUMAVG, MIN, MAX for DistributionsHAVING to Filter Aggregated ResultsGrouping by Expressions and BucketsDealing with NULLs in AggregatesLesson 4Loading CSVs into Databases: COPY, LOAD DATA, SQLite Import, and Common IssuesLearn hands-on ways to load CSV data into databases for analysis. Use COPY, LOAD DATA, SQLite import, manage separators and codes, and dodge common traps causing bad or partial loads in Nigerian data workflows.
Preparing CSVs for Sure ImportsUsing COPY in PostgreSQL and SimilarLOAD DATA for MySQL and Matching EnginesSQLite .import Steps and OptionsHandling Codes, Separators, QuotesChecking Row Counts and Rejected RecordsLesson 5DDL and DML Basics: CREATE TABLE, ALTER, INSERT, UPDATE, DELETE, Transaction ControlLearn how DDL and DML shape and change tables for analytics. Practice making and altering setups, adding and updating data, deleting safely, and using transactions to keep data solid in Nigerian analytical flows and pipelines.
Creating Analytical Tables with CREATE TABLEChanging Setups Safely with ALTER TABLEINSERT Patterns for Bulk and Step LoadsUPDATE and DELETE with Safe ConditionsCOMMIT, ROLLBACK, Transaction ScopeACID Properties in Analytical TasksLesson 6Query Basics: SELECT, WHERE, ORDER BY, LIMIT, DISTINCTMaster core query writing used in almost every analysis. Learn SELECT pulls columns, WHERE filters rows, ORDER BY sorts, LIMIT sets sample size, DISTINCT cuts duplicates in Nigerian analytical queries.
SELECT List Design and Column NamesFiltering Rows with WHERE ConditionsSorting Results with ORDER BYLIMIT and OFFSET for Sampling DataUsing DISTINCT to Remove DuplicatesBasic Query Fixing and RefiningLesson 7Joins and Set Operations: INNER, LEFT, RIGHT, FULL, CROSS, UNION, EXCEPT, INTERSECTGrasp how joins and set operations mix datasets for analysis. Learn when to use each join type, avoid copy errors, and how UNION, EXCEPT, INTERSECT aid complex Nigerian analytical comparisons.
INNER JOIN for Overlapping DatasetsLEFT, RIGHT, FULL OUTER JOIN CasesCROSS JOIN and Full Products in AnalysisUNION vs UNION ALL for Stacking DataEXCEPT and INTERSECT for Set ComparisonsSpotting and Fixing Join CopiesLesson 8Relational Database Ideas: Tables, Primary/Foreign Keys, Normalisation vs DenormalisationGrasp core relational ideas behind analytical setups. Learn tables, primary and foreign keys, normalisation levels, and when to denormalise for speed in Nigerian reporting and BI tasks.
Tables, Rows, Columns in PracticePrimary Keys and Uniqueness RulesForeign Keys and Link IntegrityNormalisation Forms and Redundancy ControlDenormalisation for Reporting SpeedStar and Snowflake Setups OverviewLesson 9Performance Basics: Indexes, Query Plans, Explain/Analyse, Simple Speed Strategies for Analytical QueriesGet a practical look at query speed for analytics. Learn how indexes work, read query plans, use EXPLAIN and ANALYSE, and apply simple speed plans to keep Nigerian analytical queries efficient.
How Indexes Speed Lookups and JoinsReading and Understanding Query PlansUsing EXPLAIN and ANALYSE in PracticeSpotting Slow Filters and JoinsOptimising GROUP BY and SummingBasic Indexing Plans for AnalyticsLesson 10Window Functions Overview: ROW_NUMBER, RANK, DENSE_RANK, SUM() OVER(), AVG() OVER(), PARTITION BYDive into window functions for advanced analytics without losing rows. Learn ranking, running totals, moving averages, and partitioning plans that drive cohort, trend, and segment analysis in Nigerian SQL work.
Window Function Syntax and OVER ClauseROW_NUMBER, RANK, DENSE_RANK CasesRunning Totals with SUM() OVER()Moving Averages with Window FramesPARTITION BY for Cohort and Segment LogicORDER BY in Windows vs Query Ordering
