A financial analyst is using SAP Databricks to build a machine learning model. They need a workspace that allows them to document their logic with narrative text while executing code in small, manageable chunks - loading data in one step, cleaning it in the next, and visualizing it immediately after. They want to share this entire workflow as a single, readable document with stakeholders. Question: Which SAP Databricks feature is designed to support this interactive, step-by-step workflow, and what are its two main components?

The analyst should use Notebooks. The two main components of a notebook are cells, which can contain either executable code (Python or SQL) or formatted text.

A data science team needs to select the best time-series algorithm for their forecasting project. They are under a tight deadline and cannot afford to manually test and tune every possible model configuration one by one. They need a method to test multiple algorithms and data preparation strategies simultaneously. Question: Which specific Python library should the team import to enable parallel processing and hyperparameter tuning for their models?

They should use the AutoTS library.

A developer is writing a Python script to automate the publishing of a new data product from SAP Databricks to SAP Business Data Cloud. The Delta Share has been created, but the developer needs to generate the specific metadata files that describe the product's capabilities and define the "official contract" of the data structure (entities, properties, and relationships) for the consumer.Question: Which two specific file types must the developer generate using Python code to satisfy these requirements before publishing?

The developer must generate an Open Resource Discovery (ORD) file and a Core Schema Notation (CSN) file.

SAP Business Data Cloud (C_BCBDC_2605) Free Practice Questions 2026

Ace the SAP Business Data Cloud C_BCBDC_2605 Exam with Free Real-World Scenario Questions [2026]

By TheExamQuestions Team 6 min read

This certification shows you know your stuff when it comes to SAP Certified - SAP Business Data Cloud, especially if you’re working with SAP Datasphere and SAP Analytics Cloud. It’s really built for data architects, consultants, and analysts who need to prove they can deliver a “business data fabric”, making sure data across the company isn’t just available, but also consistent and context-rich.

C_BCBDC Free questions.webp

Why Does This Certification Actually Matter?

The C_BCBDC_2605 exam puts your skills to the test around these key SAP data topics:

SAP Datasphere Architecture
Business Data Fabric Strategy.
Data Modeling & Integration
SAP Analytics Cloud (SAC) Synergy
Governance & Security
Space & Tenant Management

Why Does C_BCBDC_2605 Exam Use Scenario-Based Questions?

Because it’s not just about definitions. The C_BCBDC_2605 exam pushes you into real-world situations where you’ll have to pick the best modeling approach or figure out how to efficiently share data externally. You need to know how data moves through an actual business; just memorizing facts won’t cut it.

What’s in it for You Here?

We’re offering free C_BCBDC_2605 scenario questions, built to feel just like the actual exam. These questions check your technical accuracy, your grasp of the SAP Business Data Cloud, and how well you solve real client data challenges.

The Best Part?

Every question comes with a full explanation. Take a look at our latest set of SAP Business Data Cloud C_BCBDC_2605 Scenario Questions. You’ll not only see the right answers, but you’ll also understand the reasoning behind them. You start thinking like an SAP Data Architect, and you get ready for both the certification and the real world.

Now, let's jump into the C_BCBDC_2605 free practice questions.

Practice Questions

Test your knowledge with these free sample questions

Question 1

A developer is finalizing a machine learning pipeline and wants to use MLflow to track their experiments. They are using the AutoTS library to train the model. However, after running the training code, they notice that the model artifacts are not appearing in MLflow automatically, unlike in previous projects using other libraries.

Question: Why is the automatic logging failing, and what specific coding object must the developer create to successfully log the model?

Question 2

A data architect is executing the final "Innovate" phase of the Lift-Shift-Innovate strategy. The goal is to decommission legacy SAP BW workflows and replace them with native SAP Business Data Cloud components to ensure a "clean core." The architect needs to migrate the data manipulation logic currently existing in SAP BW Transformations and the virtual reporting structures currently defined as CompositeProviders. According to the recommended replacement approach, which specific SAP Datasphere objects should replace these two legacy artifacts?

Question 3

A government agency handling highly sensitive data is selecting a deployment option for SAP BW/4HANA. Their strict internal governance policies require them to have absolute physical control over the hardware, including the ability to fine-tune system-level settings for peak workloads. Furthermore, they require deep operating system-level integration for their legacy security tools, which is often restricted in managed cloud environments. Which deployment model must they choose to meet these specific compliance and technical requirements?

Question 4

A company has installed an Intelligent Application and is viewing the standard insights on their dashboard. The data science team wants to extend these results by applying advanced machine learning models to the underlying data using an external environment to generate predictive insights, which they want to display back on the original dashboard.

Question: According to the "Journey of Data," which specific external platform can the Data Product be shared with to perform this AI analysis, and how do the results return to the application?

Question 5

A global retail corporation stores its core transactional data in the SAP Business Data Cloud. The data science team wants to build machine learning models to optimize supply chain logistics. However, the Chief Information Officer (CIO) imposes a strict freeze on building any new data pipelines that require moving data out of the core system, citing concerns over data duplication, latency, and the maintenance overhead of Extract, Transform, and Load (ETL) processes.

Question: How does the architecture of SAP Databricks allow the data science team to proceed with their project while adhering to the CIO's restrictions regarding data movement and pipelines?