*We customize the course outline and content to your specific needs and relevant use cases.
Module 1: SQL basics in an insurance context
- Understanding tables, rows, columns, and keys in policy, claims, broker, and customer data
- Reading schema structures and recognizing how business entities connect
- Writing basic SELECT queries with filters, sorting, and simple conditions
- Translating common insurance questions into SQL query logic
Module 2: Working with filters, calculated fields, and data quality checks
- Using WHERE conditions for product, region, status, channel, and date based filtering
- Creating calculated fields for premiums, claim amounts, ratios, and flags
- Handling null values, missing records, and inconsistent source data
- Running simple validation checks to improve trust in query results
Module 3: Joining insurance datasets
- Combining policy, claims, broker, and customer tables with the right join type
- Understanding one to one, one to many, and many to one relationships in insurance data
- Avoiding duplicate rows and misleading totals after joins
- Building readable multi table queries for operational and reporting use cases
Module 4: Grouping, summarizing, and business metrics
- Aggregating by product, region, broker, customer segment, and time period
- Using COUNT, SUM, AVG, MIN, and MAX for insurance reporting questions
- Creating grouped views for policy volumes, claims counts, and premium totals
- Interpreting grouped outputs in a business meaningful way
Module 5: Claims analytics with SQL
- Querying claims by type, cause, reserve status, payment status, and development stage
- Building views for open claims, closed claims, aging, and settlement trends
- Calculating average claim cost, frequency measures, and simple severity patterns
- Structuring claims queries so they support dashboards and team reporting
Module 6: Policy, lapse, and retention analysis
- Querying policy lifecycle events such as new business, renewal, cancellation, and lapse
- Comparing cohorts by inception period, renewal cycle, product, and channel
- Building retention and lapse related views with date and status logic
- Preparing outputs that support portfolio and customer retention discussions
Module 7: Broker and customer analysis
- Analyzing broker performance by volume, premium, retention, and claims profile
- Segmenting customers by tenure, product holding, region, and service activity
- Linking customer and broker data to policy and claims outcomes
- Building business friendly query outputs for relationship and channel management
Module 8: SQL for recurring reporting needs
- Creating reusable query patterns for monthly, quarterly, and ad hoc reports
- Structuring result sets for export to BI tools, spreadsheets, and management summaries
- Using aliases, formatting, and query organization for readability
- Distinguishing exploratory queries from production style reporting queries
Module 9: Date logic, trends, and time based analysis
- Working with dates for policy periods, claim development, reporting cutoffs, and renewals
- Creating month over month and period over period views
- Building rolling summaries and time based comparisons
- Avoiding common mistakes in time filtering and reporting windows
Module 10: Subqueries, common table expressions, and window functions
- Using subqueries to isolate business logic step by step
- Applying common table expressions for readability and maintainability
- Introducing window functions for ranking, running totals, and partition based analysis
- Choosing the right query structure for more complex insurance questions
Module 11: Query quality, performance, and validation
- Writing queries that remain understandable for colleagues and reviewers
- Checking totals, joins, and filters for logic errors before sharing results
- Recognizing common performance issues in large insurance datasets
- Using practical habits to balance speed, accuracy, and maintainability
Module 12: From query output to business insight
- Turning query results into clear business answers and action points
- Preparing result sets for BI dashboards, actuarial review, and management reporting
- Documenting assumptions, definitions, and limitations in SQL based analysis
- Building a practical checklist for future insurance data analysis work
