SAP HANA Professional Program

• SAP HANA Professional Program is a 5-month practical training program for learners who want to understand SAP HANA as a modern in-memory database platform used for real-time analytics, S/4HANA, BW/4HANA, reporting, data modeling and enterprise data operations.

• The course begins with database fundamentals and SAP landscape awareness, then gradually moves into SAP HANA architecture, in-memory processing, SQL, SQLScript, calculation views, data provisioning, security, administration, backup, recovery, performance tuning, cloud awareness and capstone work.

• Students learn how business data is stored, queried, modeled, secured, monitored and optimized inside SAP HANA so they can understand both development and support responsibilities in SAP project environments.

• The program includes hands-on practice with SQL queries, SQLScript logic, schema design, table creation, joins, procedures, table functions, calculation views, parameters, variables, data validation and report-ready modeling concepts.

• Learners also build administration awareness through user management, roles, privileges, system monitoring, HANA cockpit concepts, alerts, traces, backups, recovery planning, high availability, troubleshooting documentation and operational checklists.

• The curriculum connects SAP HANA skills with S/4HANA, BW/4HANA, SAP BTP, SAP HANA Cloud and analytics use cases so learners understand where HANA fits in modern enterprise reporting and data-platform discussions.

• The training approach is practical and project-oriented: students create SQL scripts, calculation view designs, data loading notes, monitoring checklists, security matrices, performance case reports and a portfolio-ready SAP HANA capstone.

• By the end of the program, learners can explain SAP HANA architecture, write useful SQL and SQLScript, design basic analytical models, understand security and administration tasks, diagnose common issues and present project work confidently during interviews.

• Build the foundation for SAP HANA by understanding database fundamentals such as tables, rows, columns, keys, relationships, indexes, transactions, schemas, users and basic data storage ideas.

• Understand the SAP ecosystem including ECC, S/4HANA, BW/4HANA, SAP BTP, analytics layers, application layers, database layers and integration points across enterprise systems.

• Learn the purpose of SAP HANA as an in-memory platform designed for faster reporting, column-store processing, simplified data models and real-time analytical scenarios.

• Study how business data flows through master data, transactional data, analytical data, operational reports, dashboards and decision-support use cases.

• Become familiar with important SAP HANA tools such as SAP HANA Studio, SAP HANA Cockpit, Database Explorer, SQL Console, modeling tools and Fiori awareness.

• Understand deployment views such as on-premise HANA, appliance awareness, cloud deployment concepts, tenant databases and basic system landscape structure.

• Explore SAP HANA career roles including modeler, developer, administrator, support consultant, data analyst, analytics consultant and S/4HANA technical support.

• Learn project language such as schema, package, artifact, view, procedure, table function, transport, backup, monitoring, ticket and change request.

• Practice environment notes, schema diagrams, object lists, SQL scripts, screenshots and issue logs so documentation habits start from the first module.

• Lab outcome: explore HANA tools, identify database objects, run basic SQL, read system information and explain where HANA fits in SAP projects.

• Understand SAP HANA internal architecture including index server, name server, preprocessor, XS awareness, compile server awareness, web dispatcher and service roles.

• Learn in-memory processing concepts such as RAM-first access, columnar compression, delta storage, main storage, merge behavior and why HANA is optimized for analytics.

• Compare column store and row store concepts, including storage format, query use cases, insert behavior, compression benefit, scan performance and modeling decisions.

• Study the persistence layer including savepoints, redo logs, data volumes, log volumes, snapshots, restart recovery and durability concepts.

• Understand multitenant database containers, including system database, tenant database, isolation, resource sharing, administration and tenant lifecycle awareness.

• Learn calculation engine concepts including SQL engine, join engine awareness, OLAP engine awareness, optimizer, execution plan and query processing flow.

• Explore memory management topics such as allocation, resident memory, used memory, unload behavior, expensive statements and monitoring indicators.

• Understand scale-up and scale-out awareness with host roles, worker nodes, standby nodes, distribution, partitions and high-level sizing thinking.

• Discuss common architecture issues such as high memory use, slow queries, locked sessions, service restart, disk full risk and blocked operations.

• Lab outcome: map HANA services, compare row and column tables, review memory views and explain an end-to-end query path professionally.

• Develop strong SQL skills for querying, transforming, validating and preparing business data inside SAP HANA.

• Practice SQL basics including SELECT, WHERE, ORDER BY, GROUP BY, HAVING, DISTINCT, aliases, filters, expressions and result validation.

• Learn database objects such as schemas, tables, views, sequences, synonyms, constraints, primary keys, foreign key awareness and naming standards.

• Work with joins and set logic including inner join, left join, right join, full join awareness, union, union all, intersect awareness and data matching rules.

• Use built-in functions for string handling, numeric calculations, dates, conversions, null handling, case expressions, aggregation and practical reporting calculations.

• Understand DML and transactions including insert, update, delete, commit, rollback, transaction safety, change impact and script testing discipline.

• Learn SQLScript fundamentals such as variables, containers, control flow awareness, table variables, scalar values, parameters and readable procedures.

• Create stored procedures with input parameters, output parameters, exception awareness, reusable logic, testing steps, debugging notes and documentation.

• Build table functions for tabular output, calculation view integration, parameter passing, reusable transformations and performance-aware design.

• Lab outcome: create tables, write joins, build aggregate reports, create a procedure, create a table function and validate output data.

• Learn SAP HANA modeling concepts used for analytics, reporting, KPI calculation and reusable data-layer design.

• Understand the purpose of virtual data models, reporting layers, reusable logic, semantic definitions, business-friendly views and performance control.

• Study view types including attribute views, analytic views, graphical calculation views, SQL calculation views and the modern modeling direction in HANA.

• Practice graphical modeling with projection nodes, join nodes, union nodes, aggregation nodes, rank awareness, filters, calculated columns and restricted columns.

• Understand measures and attributes including key figures, dimensions, semantics, aggregation behavior, currency awareness, units and output field selection.

• Use parameters and variables for dynamic filtering, prompts, default values, report flexibility and reusable calculation-view design.

• Learn star join and dimension concepts including fact tables, dimension tables, master data joins, analytical queries and business reporting structures.

• Apply data quality checks for duplicate rows, missing keys, null values, incorrect joins, record count validation and reconciliation with source data.

• Discuss modeling governance such as package naming, object dependency, comments, version notes, activation checks and transport preparation awareness.

• Lab outcome: create calculation views, add joins and unions, define measures, use parameters, activate views and validate report output.

• Understand how data enters SAP HANA from SAP and non-SAP systems for reporting, migration, analytics and integration needs.

• Study integration overview topics such as source systems, target schemas, staging layers, transformations, reconciliation, scheduling, monitoring and error handling.

• Learn data loading methods including file imports, table upload awareness, SQL-based loading, data preview, validation and controlled refresh processes.

• Understand ETL and ELT concepts such as extraction, transformation, loading, cleansing, mapping, lookup, delta logic and audit fields.

• Explore SAP data sources including S/4HANA tables, BW data, CDS view awareness, extractor awareness, operational data and analytics use cases.

• Explore non-SAP sources such as flat files, databases, API awareness, external systems, connector thinking and data type mapping challenges.

• Learn SDA and virtual access awareness including remote sources, virtual tables, federation, latency, security and when virtualization is suitable.

• Understand SDI awareness including replication tasks, flowgraphs, real-time or batch movement, adapter concepts and monitoring data loads.

• Practice data governance using ownership, source-to-target mapping, lineage notes, data quality rules, duplicate checks and reconciliation reports.

• Lab outcome: load sample data, create a staging design, map fields, validate counts, design a simple data flow and document integration notes.

• Apply SAP HANA security fundamentals for protecting data, users, database objects, calculation models and administrative access.

• Learn security principles including least privilege, segregation of duties, strong authentication, secure transport, sensitive data protection and audit readiness.

• Practice user management with database users, technical users, restricted user awareness, password policy, user lifecycle, lock status and access review.

• Understand privileges including system privileges, object privileges, package privileges awareness, schema access, grant options and privilege troubleshooting.

• Study role concepts such as catalog roles, repository roles awareness, custom roles, role assignment, naming standards and access documentation.

• Learn analytic privileges for row-level control, calculation view restrictions, dynamic filter awareness, test users and reporting security design.

• Understand authentication awareness including internal authentication, LDAP/SAML awareness, certificates, secure channels and enterprise identity integration concepts.

• Explore auditing, audit policies, event tracking, login activity, privilege changes, sensitive access review and audit report interpretation.

• Discuss encryption awareness including data volume encryption, backup encryption, communication encryption, key management concepts and compliance thinking.

• Lab outcome: create users, assign roles, test object access, apply analytic privilege awareness and prepare a security access matrix.

• Learn core SAP HANA administration activities required for stable operation, support monitoring and issue investigation.

• Understand system health, services, tenants, alerts, configuration, users, licenses, workload, backups and operations calendar planning.

• Explore HANA Cockpit awareness including system overview, monitoring tiles, alerts, memory, CPU, disk, expensive statements and database administration tasks.

• Practice service monitoring for index server status, tenant status, start/stop awareness, trace files, diagnosis files and restart impact thinking.

• Understand system configuration through parameters, ini file awareness, configuration layers, change approval, restart requirement and documentation discipline.

• Learn alerts and notifications including alert categories, severity, root cause notes, escalation path, maintenance windows and response checklists.

• Study trace and diagnosis concepts including database trace, performance trace awareness, SQL trace awareness, dump files, log review and evidence collection.

• Understand job and task awareness including scheduled tasks, merge behavior, backup schedule, monitoring jobs, long-running sessions and cancellation precautions.

• Learn operational documentation such as daily checks, weekly checks, change logs, incident notes, capacity records and support handover documents.

• Lab outcome: review cockpit screens, check system health, inspect alerts, collect diagnosis notes and build an operations checklist.

• Understand data protection, restore planning and availability concepts needed for safe SAP HANA operations.

• Learn backup fundamentals including full backup, differential awareness, incremental awareness, log backup, backup catalog, retention and media planning.

• Study recovery concepts such as point-in-time recovery, complete recovery, log replay, recovery objectives, restore testing and business impact awareness.

• Understand backup configuration including backup location, schedule, storage checks, naming convention, encryption awareness and backup validation process.

• Explore snapshot awareness including storage snapshots, consistency, integration with backup strategy, advantages, limitations and operational cautions.

• Learn system replication concepts such as primary and secondary system, sync modes awareness, takeover, failback, replication status and monitoring checks.

• Understand high availability concepts including host auto-failover awareness, standby host, service restart, failover testing and cluster awareness.

• Learn disaster recovery planning with RPO, RTO, DR site, network dependency, storage dependency, runbook, contact matrix and test schedule.

• Discuss common issues such as missing log backup, storage full, failed backup, catalog inconsistency, replication lag and untested restore process.

• Lab outcome: design a backup schedule, read backup catalog examples, create a recovery checklist and prepare HA/DR scenario documentation.

• Develop a performance mindset for SQL, calculation views, memory behavior, workload analysis and structured troubleshooting.

• Learn a troubleshooting method: define the symptom, gather evidence, isolate the layer, compare baseline, test safely, apply fix, verify improvement and document results.

• Improve SQL performance through filters, joins, aggregation, index awareness, calculation pushdown, avoiding unnecessary columns and efficient query patterns.

• Understand execution plans, operator reading, cardinality thinking, expensive step identification and optimization clues.

• Investigate expensive statements using monitoring views, runtime, memory, CPU, frequency, user, application source and prioritization for investigation.

• Tune calculation views through pruning, filter pushdown, join cardinality, aggregation behavior, input parameters and avoiding duplicate record explosion.

• Troubleshoot memory issues such as high memory use, unload behavior, delta merge, statement memory, temporary results and capacity monitoring indicators.

• Understand data loading performance, batch size awareness, locks, commit frequency, staging design, transformation placement and reconciliation trade-offs.

• Discuss system issues such as blocked transactions, locks, long sessions, disk pressure, CPU load, network latency and failed jobs.

• Lab outcome: tune sample queries, inspect expensive statements, optimize a calculation view and write a performance case report.

• Connect SAP HANA database skills with enterprise analytics, S/4HANA simplified data models and business reporting layers.

• Understand the S/4HANA relationship with HANA as the database layer supporting simplified tables, real-time reporting, embedded analytics and operational data processing.

• Learn CDS view awareness including virtual data models, annotation awareness, analytical queries, authorization checks and reporting consumption concepts.

• Understand BW/4HANA awareness including data warehouse purpose, ADSO awareness, composite provider awareness, transformations and analytical reporting layers.

• Study analytics architecture including source tables, models, semantic layers, calculation views, reporting tools, dashboards and business KPI delivery.

• Discuss reporting use cases such as sales analysis, inventory analysis, finance reporting, customer insights, supply chain metrics and management dashboards.

• Practice data reconciliation with source counts, transformation rules, aggregate validation, business totals, drilldown review and exception analysis.

• Explore tool awareness including SAP Analytics Cloud, BusinessObjects awareness, SQL reporting tools, Excel connectivity awareness and data preview checks.

• Learn security in analytics such as user access, analytic privileges, row restrictions, sensitive measures, data masking awareness and dashboard sharing controls.

• Lab outcome: map S/4HANA-to-HANA reporting flow, design an analytical view, validate KPI output and prepare analytics documentation.

• Build awareness of cloud-based SAP HANA environments and how modern teams use SAP BTP for data and application scenarios.

• Understand SAP HANA Cloud as a managed cloud database service, including provisioning awareness, scaling, availability and operational model.

• Learn SAP BTP concepts such as subaccounts, spaces awareness, services, entitlements, destinations, connectivity, identity and application integration.

• Study cloud connectivity including secure tunnel awareness, cloud connector concepts, private access, public access control and hybrid landscape thinking.

• Understand data lake awareness including warm data, storage tiering ideas, large-scale analytics, cost control and separation of hot and historical data.

• Compare administration differences such as cloud monitoring, managed backups, updates, scaling options, metrics, alerts and responsibility split.

• Learn security in cloud with identity providers, roles, encrypted communication, network restrictions, secrets management and access review habits.

• Discuss migration awareness including assessment, schema movement, data transfer, compatibility checks, downtime planning, testing and rollback notes.

• Explore development awareness including database explorer, HDI containers, cloud schemas, service bindings and application data access patterns.

• Lab outcome: design a HANA Cloud landscape diagram, map connectivity, document access controls and compare on-premise versus cloud operations.

• Complete the course with a portfolio-ready SAP HANA project, support practice, interview preparation and presentation confidence.

• Plan the capstone using business requirements, source data, schema design, tables, modeling approach, security needs, reporting output and milestone tracking.

• Build the project by creating schemas, loading data, writing SQL, building calculation views, adding parameters, validating output and preparing a demo flow.

• Prepare administration evidence including user access matrix, monitoring checklist, backup strategy note, performance review note and troubleshooting summary.

• Practice support-ticket handling by classifying issues, gathering evidence, reproducing problems, analyzing root cause, proposing fixes, verifying results and communicating status clearly.

• Build a documentation package with README, architecture diagram, object list, SQL scripts, view screenshots, validation report, issue log and known limitations.

• Review interview topics such as HANA architecture, column store, SQLScript, calculation views, security, backup, performance, S/4HANA, cloud and support scenarios.

• Practice scenarios such as slow report, authorization failure, failed load, high memory, backup issue, activation error, wrong aggregation and missing data.

• Prepare resume direction for SAP HANA modeler, database support, junior SAP consultant, analytics support, S/4HANA technical support and data platform roles.

• Final outcome: present a complete SAP HANA solution with working models, SQL evidence, reports, security notes and professional explanation.