C_HAMOD_2601 Exam Guide: Data Access, Calculation Views & Exam Preparation

# C_HAMOD_2601 Exam Guide: Data Access, Calculation Views & Exam Preparation ![](https://codimd.avt-imt.de/uploads/8674bf6d-6883-4f45-88cd-2ace97d54bad.png) ## Quick summary The C_HAMOD_2601 exam guide covers the two areas of the SAP HANA data engineer assessment: Data Access and Calculation Views, each weighted 41 to 50%. The system-based test runs three hours with a 60% pass score. Practise remote sources, virtualization, replication, flowgraphs, and calculation view modelling in SAP HANA Cloud to build the skills the assessment rewards. ## Introduction Data engineering in SAP HANA covers how information enters the system, how sources connect, and how raw records become models for reporting and analysis. The SAP Certified Associate - Data Engineer - SAP HANA certification validates those capabilities across data provisioning and data modelling in SAP HANA Cloud and SAP HANA. This [C_HAMOD_2601 Exam Guide](https://theexamquestions.com/blog/c-hamod-sap-exam-guide) works as a technical reference for reviewing the main concepts, tying them into complete workflows, and building practical confidence before exam day. ## C_HAMOD_2601 exam overview SAP lists the certification under the code C_HAMOD. The label 2601 serves as the search phrase for this guide, so confirm the version shown in your own SAP certification account before booking. | Exam detail | Current information | |---|---| | Certification | SAP Certified Associate - Data Engineer - SAP HANA | | Exam code | C_HAMOD | | Assessment type | System-based assessment | | Activities | One | | Duration | Three hours | | Pass score | 60% | | Topic area | SAP-listed weight | |---|---:| | Data Access | 41 to 50% | | Calculation Views | 41 to 50% | Both ranges call for substantial preparation time. SAP publishes weights for the two areas only, so treat the detailed subjects below as a revision checklist rather than a breakdown of individual question weights. ## Data access in SAP HANA Data access describes how SAP HANA obtains and works with information from other systems. Strong candidates explain the practical differences between reading remote data, replicating it, and transforming it. ### Remote sources and connections A remote source is the connection between SAP HANA and an external system. Practise creating remote sources through the interface and with SQL, identifying connection details, and checking that a connection works. ### Virtual tables and data virtualization A virtual table gives access to remote data while the data stays in its source system. Review virtual tables in classic schemas and HDI containers. Virtualization reads data where it lives, while replication brings data into the target environment. ### Data replication Replication transfers source data into SAP HANA, which supports local availability and repeated analysis. Study replication tasks, replication services, SQL-based operations, and validation of replicated records against the source. ### Data transformation with flowgraphs Flowgraphs design processes that change, filter, combine, and organize data. Practise with a small dataset holding inconsistent records: build a flow that prepares the data, then inspect the output. ## Calculation views in SAP HANA Calculation views sit at the center of data modelling. They combine information from several sources into reusable models for analytical queries. Success here comes from knowing each modelling operation and linking them into a working model. ### Modelling environment Become comfortable with the SAP HANA modelling environment, including project and content management in SAP Business Application Studio. ### Common calculation view nodes | Node | Main purpose | |---|---| | Projection | Selects required columns | | Join | Combines related records through matching fields | | Union | Appends compatible datasets into one result | | Filter | Restricts records by condition | | Aggregation | Summarizes data with measures and grouping fields | A join combines related columns from matching records, while a union appends compatible records from different datasets. ### Calculated columns and functions Calculated columns derive values from existing data. A sales model holding quantity and unit price can derive order value with the expression `Quantity * UnitPrice`. Check data types, null values, and calculation logic, and review embedded functions and custom SQL logic for advanced requirements. ### Data slices, ranking, filters, and hierarchies Analytical models often show a subset of records or rank them by a measure, such as the highest-value orders for a selected region. Dynamic calculation views respond to reporting requirements, and hierarchies organize related values into levels so users can explore data at different depths. ## How the two areas connect Picture a business with product information in one system and sales transactions in another, aiming to analyze sales by category and region. The data engineer identifies the sources, configures remote sources, chooses between virtualization and replication, and makes the tables available. A calculation view then joins products with sales through the right key, adds a total order value measure, applies filters and aggregations, and gets validated against sample records and expected totals. Data Access supplies the information, and Calculation Views shape it into an analytical structure. ## Practical preparation strategy Follow the [SAP official certification](https://learning.sap.com/certifications/sap-certified-associate-data-engineer-sap-hana) page as the foundation of your plan, since it covers data modelling, data provisioning, project and content management, remote sources, virtual tables, transformation, and replication. Build a practice environment and work through provisioning, then confirm that connections work, records arrive, and transformations deliver expected results. Create calculation views gradually: start with a projection, add joins, unions, filters, calculated columns, and aggregations, then advance to ranking, functions, dynamic views, and hierarchies. Revisit SQL throughout, then repeat complete workflows from source access through transformation, modelling, and validation. ## Frequently asked questions ### What is the C_HAMOD_2601 exam guide about? It is a technical preparation reference for the SAP Certified Associate - Data Engineer - SAP HANA assessment, centered on data access, data provisioning, and calculation views. ### What topics does the C_HAMOD exam include? Data Access and Calculation Views, each listed at 41 to 50% on the SAP certification page. ### How long is the C_HAMOD exam and what score passes? SAP lists a three-hour duration and a 60% pass score. Confirm both on the live exam page before scheduling. ### Is C_HAMOD a system-based assessment? Yes. SAP lists one activity, so hands-on familiarity with SAP HANA forms an important part of preparation. ## Final revision advice The C_HAMOD assessment rewards practical data engineering capability. Cover both exam areas, spend enough hands-on time to see how operations fit into a complete workflow, and validate every output before moving on. For additional SAP certification practice and study references, visit [The Exam Questions](https://theexamquestions.com/).