SAP HANA Implementation, Modelling and Reporting Course

Register for SAP Hana express edition, set up a virtual machine image in Oracle VirtualBox, then connect via the web id to mount system and tenant and review tenant persistence.

Configure and start the Hana database within a VM, managing memory constraints and prompts as you log in, set passwords, and initialize web services.

Edit the Windows hosts file to map the Hana server IP, then test by logging into Web IDE as admin and verifying the landing page.

Mount your SAP HANA database on WebIDE by mounting the system database and an optional tenant. Log in with the system user to view schemas.

Map the development space to a specific tenant database to avoid defaulting to the system db and ensure artifacts persist in the designated tenant, such as ZK, via HDI.

Jump into Hana modeling by exploring dimensions, facts, and cube concepts, then build your first purchase insights cube using curated data, joins, and semantic layer exploration.

Explore the fundamentals of modeling for SAP analytics, distinguishing transactions and dimensions, and learn how normalized data models, keys, and joins support real time reporting across data sources.

Access the SAP HANA Web IDE, verify the HANA database runs on GCP, authenticate via the URL with admin and the master password, and explore workspace and the database explorer.

Build views from the employee, business partner, address, and product tables to model the dataset, then create a calculated column, an EMEA region filter, and a purchase cube for reporting.

Create a SAP Hana project and import data from a zip of CSV files using the table import method. Build the project to generate tables and verify data in container.

Import and configure a SAP HANA project by creating a development workspace, building the HDI container, and importing data, resources, and models to reveal tables and views.

Explore the Hana database's regular joins, including 1 to 1, one to many, many to one, and many to many, and see how cardinality boosts optimization and accuracy.

Master inner joins for 1-1 and 1-to-n cardinalities by linking addresses with business partners in Hana, and execute the SQL join in the HDI environment.

demonstrates an inner join between products and business partners in a one-to-many relationship, producing 106 rows and illustrating primary and foreign keys guiding the join.

Learn left outer join theory and hands-on practice by joining address and business partner tables in Hana to see how the left table drives matches and nulls.

Demonstrate right outer join capabilities in SAP HANA by joining business partner and address tables on address_id, showing all address records even when partner data is missing.

Explore full outer join theory and hands-on practice with SAP HANA, linking address and business partner data to reveal matches and missing information.

Explore referential joins in Hana, inner joins with special characteristics, and prerequisites like central table maintaining referential integrity and one-to-n cardinality toward transaction tables.

Create a standard dimension calculation view for employees in SAP HANA, selecting required columns, setting employee ID as the key, then build, save, and preview the data.

Create a partner dimension calculation view by projecting and left outer joining business partner and address tables, then define calculated column Firm name by concatenating company name and legal form.

Create a hybrid dimension calculation view by joining a products table and a partners view, projecting all columns, and filtering to the EMEA region.

Build a SAP HANA purchase queue by creating a calculation view with a star join that blends purchase order header and item with employee and product dimensions.

Explore how the semantic layer uses the semantics node to shape the reporting view in cube and dimension calculation views, with shared columns and semantics for measures and attributes.

Learn to work with SAP HANA nodes—projection, join, and star join—covering mapping, calculated columns, parameters, filter expressions, and restricted columns for optimized reporting.

Implement restricted columns to enable rule-based access at the tuple level, restricting the base measure gross amount by country (Germany, Great Britain) using include or exclude options on star join.

Navigate smart data integration with Hana 2.0 and SDI/A, install components, import data, and build ETL flows. Configure access, user interface, yaml, and grants, then explore project-based cube and cdc.

Log in to the HANA server, free memory to install SDI components, download and install the HDI, then validate by running an empty project in the Web IDE.

Learn to test SAP HANA HDI by importing the S flight data model, creating an MTA project, and building virtual tables and ETL flows.

Create a remote source in the SAP HANA catalog using the Hana adapter, name it Hana DB, configure the host, port, instance number, and credentials, then finalize the remote source.

Create an MTA-based SAP HANA project for ETL, add a HANA database module, build an HDI container with the template’s UI components, then mount and explore it in the workspace.

Set up a UI service to connect a tenant to the HDI by creating a user provider with driver, username, and password, then save to establish the connection.

Create a virtual table by selecting a virtual connection, naming with a VR ETL prefix, and building design-time objects for tables, book and as custom, in the HDI ETL environment.

Test an empty SDI flow graph by creating a new ETL flow named test, connecting a HANA object virtual table to a template table, and executing to populate the target.

Configure your SAP HANA environment by creating a remote connection, a virtual table, and the Gruntfile, then import and run pre-built SGI flow graphs FG1 and FG2.

The course demonstrates building a base cube in an HDI project, showing staging tables, projection, region-based slicing, unions, joins, and aggregations of customer and transaction data.

Create a subfolder in the ETL flow and a flow graph FG1 to project, cleanse addresses in HDI data, and create a discount abs column, then write a template table.

Execute a projection on the book transaction data by adding quarter and day name columns, removing unused fields, and applying a year filter to isolate 2010 reporting.

Apply a case transform to split data by regions and route us, fr, and default outputs to separate targets. Test with projections and truncate settings to verify segmentation.

Use a union node to combine Germany, the US, and France into a single union output for a staging table, ensuring identical columns and metadata.

Join the union and the transaction data with a join node, using an inner join on customer ID, and output to cube_join staging table for multi-dimensional analysis.

Apply an aggregate transform to roll up measures for reporting, filter by country, and produce customer-level totals via the join node.

Explore change data capture for maintaining master data like customers, with a projection node and table comparison to capture inserts, updates, deletes and history for compliance.

Analyze the current source table by creating a Berlin-filtered subset. Implement CDC in SAP HANA to capture changes and preserve history in a capture history table.

Create a Berlin-filtered subset of the customer table in the split schema, then implement change data capture in SAP HANA to track and preserve history.

Create a virtual table at the source level pointing to the customer source table in your tenant, persist changes to the HDI, and verify by opening data.

Create a namespace at the ETL flows level to organize project artifacts in per-project subfolders, persist changes, and build the project to ensure the correct folder path and ignored subfolders.

Set up capture table with a CDS artifact to capture changes from customer table, preserving history, using a surrogate key plus a composite key, record type, change time, and validity.

Create a sequence in the hdi space to generate the surrogate key for the target cdc table within the etl flow and test by running the flow.

Create a table comparison flow to capture changes from a virtual source to a CDC target, monitor id, name, and email, and configure insert-based history with surrogate keys.

Use history preserving for CDC to track insertions and updates with a status flag and valid from and valid to dates, capturing new and old records during each data change.

Develop the second modeling project for the sales insights use case, build the sales insights cube with a layered approach using dimension and cube calculation views, and complete a quiz.

Build and unite 2014 and 2015 sales cubes in SAP HANA, apply currency conversion, ranking, temporal and spatial joins, and implement hierarchies and text join for flexible reporting.

Import data into SAP HANA by creating a data folder, loading csv files into merge tables for 2014 and 2015, and union the transaction data with dimension information.

Import data and views into the same project by creating data and models folders, importing merge sales order 2014 and 2015 tables, and building and previewing HDI artifacts and views.

Create a dimension calculation view that joins address and business partner data in the HDI, projecting all columns with a 1-to-1 inner join and validating via data preview.

Create a 2014 cube calculation view by projecting 2014 transaction data, joining with a business partner dimension, mapping columns, adding a year calculated column, and validating with data preview.

Copy the 2014 cube, rename it to 2015, replace the transaction table with the 2015 data source, map 1-to-1, refactor, build, and preview the 2015 data.

Create a calculation view to union 2014 and 2015 cubes, auto map by name, designate quantity, tax amount, net amount, and gross amount as measures, then preview the merged data.

Filter a data cube to include only EUR transactions on specific dates by applying a currency filter in the aggregation node, then validate and build the view.

Create an input parameter to capture the user’s currency choice, set as mandatory with a direct value and a default of USD, and preview data before binding for currency conversion.

Add a currency conversion column by duplicating the gross amount in cubes 2014 and 2015, naming it gross_target, and uniting the cubes for output.

Configure currency conversion for a selected column by assigning semantics to amount with currency code, using the conversion tables, and set the target currency via input parameter (default USD).

Build the ranking feature to identify top and bottom performers across country, region, or product line, explore absolute values and percentages, and experiment with rank, dense rank, and row aggregations.

Create and configure a rank node from a cube source, selecting country and gross amount, and apply absolute rank with top five, generating a score column partitioned by country.

Apply dense rank with a percentage result type to show top percentages (e.g., 0.5 for top 50%) across countries and companies, using build, save, and refresh to update the data.

Execute a temporal join between sales order transactions and the business partner address, using a star join on a cube, constrained by validity start and end dates.

Learn to implement a spatial join on geo data by joining an address table on the point spatial column using equals predicate in a SAP HANA calculation view.

Build a region, country, and city level hierarchy from the address table. Configure nodes and route handling in a calculation view, then test with a BI tool using MDX.

Explore model optimization and accuracy in SAP HANA, using performance analysis tools, explain plans, and data lineage to reduce data vertically and horizontally, avoid unnecessary joins, and maintain accurate results.

Explore fundamentals of SAP HANA data modeling for optimized, accurate reporting, from raw data projection through filters, joins, and aggregations, focusing on early row and column reduction and appropriate cardinality.

Navigate the performance analysis mode to review source table details and join validations, and identify warnings about calculated columns or filters that affect performance.

Use debug mode to simulate the application level query, inspect data and intermediate results, and understand column pruning across calculation views and their dependent views.

Explore explain plan to see how the Hana database will execute a query, including operator details, source data, output size, and execution cost, with plan and connection IDs for analysis.

Explore SAP HANA visualize plan to analyze SQL performance, drill into operator-level bottlenecks, data flow, and costs, and optimize query structure using logical and physical plan insights.

Demonstrates vertical and horizontal filtering, reducing columns and rows, to boost query performance, lowering time from about 300 ms to ~37 ms, with plan graph insights.

Discover how avoiding unnecessary joins in SAP HANA reporting—by pruning unused columns and using explain plan—dramatically improves query performance.

Learn to boost performance with union pruning by implementing a constant hinting column in a 2014–2015 union, enabling where-clause filtering to skip unnecessary data and reduce joins.

Explore Hana optimization features to boost query performance by unfolding calculation views into SQL expressions, enabling the SQL engine, and leveraging optimization, dynamic join, and denormalization with accuracy considerations.

Explore data lineage to trace how a view's data flows from source tables and cubes through semantics and columns, enabling impact analysis and troubleshooting.

Explore SAP HANA 2.0 security fundamentals, including web, high-level, and database user access; create a user, grant analytic privileges on the HDI model, test, and review docs.

Learn the SAP HANA 2.0 security model by focusing on securing models in your schema, understanding three key user types, and applying object, system, and analytical privileges through roles.

Explore how the current security layout controls access to SAP HANA artifacts, showing the roles of system and technical users, HDI, privileges, and the consumption point from the tenant.

Create a new user in the SAP HANA cockpit, enforce first-login password change, and assign schema privileges and a role to enable scoped access.

Create a role named access schema to grant select and execute privileges on an HDI schema, assign the role to the user, and verify access by viewing tables and data.

Enable SQL analytic privileges at the model level to restrict data access, build the privilege, and assign it to a user or role to protect underlying data.

Create an analytic privilege for the Z sec model to grant a user access, set a validity date, and restrict data to EMEA region with drill to region and country.

Create and assign an analytic privilege named ana sec to a runtime role, then test access to ensure a user sees only EMEA data in the cube.

Learn the essentials of version control and model operation with git for Hana database projects, including setting up local and remote repositories, merging changes, and pushing updates to environments.

Git lets teams work on a central repository by creating local repositories, using branches (feature, develop, release, hotfix), and frequently pulling, committing, and pushing changes to maintain production integrity.

Learn to set up a new project, initialize a local git repository, and manage commits using the git pane and history in a SAP HANA database environment.

Create and track simple test files, stage and commit changes with clear messages, and review history to understand versioning and comparisons in the main branch of a local git repository.

Learn how to create a local branch, commit changes, and merge them into the master branch in a Git workflow, illustrating branch isolation, merging, and history tracking.

Clone a git repository from GitHub, create and manage repositories (public or private), commit and push changes to the main branch, and connect via the SAP HANA Web IDE.

Create a new SAP HANA project, connect a local repository to a remote GitHub repository, then commit, fetch, and merge to import calculation views and MTA files.

Push local changes to remote repository after committing updates to the XML file, demonstrating version control with commit and push and reflecting email v1 and last name v1 on GitHub.

Create a new remote branch from master, stage and commit a file, then push changes to the remote repository, illustrating remote branch creation and an initial commit.