SQL Server Data Querying and Analysis Training Course

Course overview

Teams often hold the data needed to explain sales movement, service performance, stock availability, operational delays and customer behaviour inside SQL Server databases, yet rely on manual extracts or wait for specialist support. This course equips professionals to retrieve, combine, validate and interpret that data using Transact-SQL (T-SQL). Participants learn how to turn a business question into a repeatable query, avoid misleading results caused by duplicate rows or incorrect joins, and produce evidence that managers can use in operational decisions.

Across five days, the course builds practical SQL Server querying capability from relational foundations through to analytical reporting. Participants work with SELECT statements, filters, calculated columns, joins, aggregations, subqueries, common table expressions (CTEs), window functions, date handling and data-quality checks. They also learn to inspect query execution plans, apply appropriate indexes and rewrite inefficient queries. Later sessions focus on designing reusable views and stored procedures, parameterising reports, and preparing SQL Server outputs for Power BI analysis.

Delivery combines instructor demonstrations in SQL Server Management Studio with guided lab work against realistic business datasets. Each day ends with a focused exercise, progressing from simple customer and order queries to an end-to-end operational analysis. Participants leave with a reviewed SQL query portfolio: documented scripts, a reusable reporting view, a parameterised stored procedure and a short analysis brief based on a business case. The course is available as a five-day classroom programme or live online instructor-led training, with a certificate issued on completion.

Course objectives

By the end of this course, participants will be able to:

• Write T-SQL SELECT statements using filters, aliases, expressions and NULL handling
• Join SQL Server tables with inner, outer and self-join methods while preventing duplicate results
• Aggregate and segment business data with GROUP BY, HAVING and conditional calculations
• Build reusable analytical queries with subqueries, common table expressions and temporary tables
• Calculate rankings, running totals and period comparisons with window functions
• Validate query outputs through row-count reconciliation, duplicate detection and data-quality checks
• Diagnose slow queries using execution plans, logical reads and index recommendations
• Produce a documented reporting view, parameterised stored procedure and analysis brief

Benefits of attending

Target competencies

Who should attend

• Data Analysts — who need to answer business questions directly from SQL Server data
• Business Intelligence Analysts — who prepare reliable datasets for dashboards and recurring reports
• Reporting Analysts — who must replace manual spreadsheet extracts with repeatable SQL queries
• Junior Database Developers — who need a practical foundation in T-SQL querying and performance
• Business Systems Analysts — who investigate operational data and validate system reporting
• Operations Managers — who need to interrogate team data and specify robust reporting requirements

Requirements and prerequisites

Participants should be comfortable using a Windows desktop environment, working with files and spreadsheets, and interpreting basic business measures such as totals, averages, dates and percentages. No previous SQL programming is required: the course starts with tables, rows, columns, keys and simple SELECT statements. Familiarity with relational databases, Microsoft SQL Server, SQL Server Management Studio or Power BI is helpful but not assumed. Complete beginners should expect structured practice with SQL syntax each day and should be prepared to work through hands-on exercises rather than observe demonstrations only. No database administration, coding background or advanced mathematics is required.

Training methodology

The instructor introduces each T-SQL technique through a short live build in SQL Server Management Studio, then participants apply it in individual labs using linked sales, customer, product and service tables. Exercises deliberately include duplicate records, missing values and inefficient queries so that validation and troubleshooting become part of the workflow. Small-group case discussions focus on translating reporting requests into query specifications. On day five, each participant assembles an end-to-end analysis pack and records how the approach will be applied to a live workplace reporting need.

Course outline

Day 1: Relational data and essential T-SQL

• SQL Server database objects, schemas, tables and relationships
• SELECT statement structure and result-set design
• Column aliases, calculated fields and data type conversion
• WHERE filtering with comparison, logical and pattern operators
• Sorting, TOP and pagination with ORDER BY and OFFSET FETCH
• NULL values, three-valued logic and COALESCE handling
• Primary keys, foreign keys and reading table metadata

Workshop: Participants profile a sales database and produce a documented set of filtered customer, order and product queries for a reporting request.

Day 2: Combining and summarising business data

• INNER JOIN and LEFT JOIN relationship patterns
• RIGHT JOIN, FULL OUTER JOIN and self-join use cases
• Join cardinality and diagnosing duplicate row multiplication
• UNION, UNION ALL, INTERSECT and EXCEPT set operations
• Aggregate functions including SUM, AVG, MIN, MAX and COUNT
• GROUP BY, HAVING and conditional aggregation with CASE
• Date parts, date arithmetic and reporting-period filters

Workshop: Participants build a monthly sales and customer activity report, reconcile its totals and identify records that create duplicate results.

Day 3: Analytical query patterns and data validation

• Scalar and correlated subqueries
• Common table expressions for staged query logic
• Temporary tables and table variables for intermediate results
• CASE expressions for business rules and data categorisation
• ROW_NUMBER, RANK and DENSE_RANK window functions
• Running totals, moving averages and LAG LEAD comparisons
• Duplicate detection, exception reporting and row-count reconciliation

Workshop: Participants create a customer performance analysis that ranks accounts, calculates period-on-period movement and flags data-quality exceptions.

Day 4: Efficient and reusable SQL Server reporting

• Reading actual execution plans and identifying expensive operators
• Logical reads, statistics IO and common query bottlenecks
• Clustered and nonclustered indexes for query access paths
• SARGable predicates and avoiding non-searchable filters
• Views for reusable reporting datasets
• Stored procedures and input parameters
• Query parameters, plan reuse and safe dynamic SQL principles

Workshop: Participants tune a slow operational report, compare execution plans before and after changes, and publish the final logic as a parameterised stored procedure.

Day 5: Delivering trusted analysis from SQL Server

• Translating business questions into query specifications
• Defining measures, dimensions, grain and reporting assumptions
• Creating reporting views for Power BI consumption
• Import and DirectQuery considerations for SQL Server sources
• Validating dashboard extracts against source totals
• Documenting query logic, assumptions and data limitations
• SQL Server permissions and least-privilege reporting access

Workshop: Participants complete an end-to-end operational analysis case, delivering a documented SQL reporting view, parameterised procedure and manager-ready findings brief.

Tools & standards covered

Microsoft SQL Server 2022, SQL Server Management Studio, Azure Data Studio, Microsoft Power BI Desktop

A typical training day

Live online deliveries follow the same structure in the East Africa Time zone, with shorter screen blocks and longer breaks.

What the fee includes

How you can take this course

Certification

Participants who complete the full five days receive the Skillset Development Certificate of Completion, stating the course title, course code, dates and delivery format — suitable for professional-development records and employer reimbursement.

Frequently asked questions