Database Systems for Banking Data Management Training Course

Course overview

Banking teams depend on accurate, traceable data to process payments, manage customer relationships, calculate exposure, investigate suspicious activity and produce regulatory reports. Yet many operational and technology professionals work with fragmented customer, account, transaction and product data held across core banking platforms, data warehouses, CRM systems and reporting extracts. This creates duplicate records, inconsistent definitions, slow reconciliations and avoidable control failures. This course addresses the practical database knowledge needed to design, query, govern and improve banking data environments without treating banking data as generic corporate information.

Participants learn how relational database systems support core banking, lending, cards, payments, treasury, risk and compliance operations. They build entity-relationship models for customers, accounts, facilities, transactions and counterparties; write SQL queries for balances, exceptions, reconciliations and management reporting; and apply normalisation, indexing, constraints, access controls and audit logging. The course also examines banking-specific data challenges including customer identifiers, account hierarchies, transaction status, data lineage, retention, reference data and ISO 20022 payment-message structures.

Instruction combines expert-led explanation with guided SQL labs, banking data model workshops and realistic cases involving duplicate customer records, failed payment investigations and regulatory reporting extracts. Participants work with a structured sample banking database using PostgreSQL and pgAdmin, then translate the techniques to their own platforms. Each participant leaves with a banking database design pack containing an entity-relationship diagram, data dictionary, SQL query set, data-quality rules and a prioritised improvement plan that can be used in a workplace discussion with technology, operations and risk stakeholders.

The course is suited to banking professionals who need to work confidently with data teams, databases or reporting systems, as well as junior technical staff moving into financial-services data roles.

Course objectives

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

• Model customer, account, product, transaction and counterparty entities in a banking entity-relationship diagram
• Write SQL SELECT, JOIN, GROUP BY and window-function queries for banking balances, exceptions and reconciliations
• Apply normalisation rules to reduce duplicate customer and account data while preserving operational reporting needs
• Define primary keys, foreign keys, check constraints and referential-integrity controls for banking records
• Create indexes and interpret query execution plans to improve retrieval of high-volume transaction data
• Design data-quality rules for customer identifiers, transaction statuses, account dates and monetary values
• Implement role-based access, audit logging and retention controls for sensitive banking data
• Produce a banking database design pack containing a data dictionary, SQL extracts and improvement recommendations

Benefits of attending

Target competencies

Who should attend

• Banking Operations Analysts — who investigate payment, account and reconciliation exceptions using operational data
• Business Analysts — who translate banking process requirements into data models, fields and validation rules
• Data Analysts — who need reliable SQL methods for banking reporting, customer analysis and control testing
• Junior Database Administrators — who support banking databases and need sector-specific data-control context
• Risk and Compliance Analysts — who assess data lineage, retention, access and evidence for regulatory reporting
• Technology Project Managers — who oversee core banking, payments or data-platform changes and need to challenge data design decisions

Requirements and prerequisites

Participants should be comfortable using spreadsheets and navigating structured business data such as account lists, transaction extracts or customer records. Familiarity with basic banking terms including customer, account, transaction, balance, payment and reconciliation is helpful. No prior database administration experience is required, and participants do not need to know programming, advanced mathematics or a specific core banking platform. Complete beginners should expect an intensive introduction to relational concepts and SQL on the first two days, with guided exercises before working independently. A laptop is recommended for live online delivery and useful for classroom labs.

Training methodology

The course uses short instructor-led demonstrations followed by guided labs on a sample retail and corporate banking database. Participants model customer-to-account relationships, write and test SQL queries in PostgreSQL, and diagnose data-quality failures in payment and reconciliation scenarios. Small-group workshops examine trade-offs between operational processing, reporting and regulatory retention. The instructor reviews query outputs and data models with participants, linking each technique to core banking, payments or risk use cases. On the final day, each participant completes an application plan and assembles a workplace-ready database design pack.

Course outline

Day 1: Banking data foundations and relational design

• Core banking data domains: customer, account, product, transaction and counterparty
• Relational database architecture for operational systems and reporting stores
• Tables, rows, columns, schemas and database instances
• Primary keys, surrogate keys and business identifiers in banking records
• Entity-relationship diagrams for customer-to-account and account-to-transaction relationships
• Cardinality, optionality and account ownership structures
• Data types for currencies, dates, identifiers, balances and transaction amounts

Workshop: Participants produce an entity-relationship diagram for a bank account and transaction database, including keys, relationships and mandatory fields.

Day 2: SQL for banking operations and reporting

• PostgreSQL and pgAdmin query workspace orientation
• SELECT statements, aliases and calculated banking fields
• WHERE filters for dates, transaction statuses, currencies and account states
• INNER JOIN and LEFT JOIN patterns for customers, accounts and transactions
• GROUP BY, HAVING and aggregate functions for balance and volume analysis
• CASE expressions for exception categorisation and operational reporting
• Window functions for running balances, duplicate detection and transaction sequencing

Workshop: Participants write a SQL query set to identify dormant accounts, high-value transactions and unreconciled payment items.

Day 3: Data quality, integrity and reference data

• First, second and third normal form in banking data structures
• Foreign keys, unique constraints and check constraints
• Customer identity matching and duplicate-record detection
• Reference data management for currencies, countries, product codes and transaction statuses
• Data profiling techniques for nulls, invalid dates and out-of-range monetary values
• Business validation rules for account opening, transaction posting and closure dates
• Data dictionary structure, field definitions and ownership assignments

Workshop: Participants profile a flawed customer and account extract, define validation rules, and produce a data-quality issue log.

Day 4: Performance, security and banking data controls

• Index design for customer searches, account lookups and transaction-date queries
• Query execution plans and identification of costly SQL operations
• Partitioning concepts for high-volume transaction history
• Role-based access control for operations, analysts, administrators and auditors
• Database audit trails and evidence for data changes
• Data retention, archival and deletion requirements for banking records
• Data lineage from source transaction through reporting extract and regulatory submission

Workshop: Participants review a slow transaction query and an access-control scenario, then recommend indexes, roles and audit controls.

Day 5: Payments, reporting and workplace application

• ISO 20022 payment-message data concepts and transaction status fields
• Payment exception investigation using linked transaction and account records
• Reconciliation query patterns for ledger, payment and settlement data
• Regulatory reporting extracts and traceable data lineage
• Operational versus analytical database design trade-offs
• Banking database change requirements and acceptance criteria
• Database design pack structure and prioritised remediation planning

Workshop: Participants complete a banking data case study and produce a database design pack with an ERD, SQL extracts, controls and a 90-day improvement plan.

Tools & standards covered

PostgreSQL, pgAdmin 4, Microsoft SQL Server, ISO 20022

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