Why you should use SAP BW On HANA Test Online Test?

The SAP BW On HANA Test makes use of scenario-based questions to test for on-the-job skills as opposed to theoretical knowledge, ensuring that candidates who do well on this screening test have the relavant skills. The questions are designed to covered following on-the-job aspects: Ability to perform data modeling in SAP BW Proficiency in SAP HANA architecture and technology Experience with ETL processes in SAP BW Knowledge of data modeling concepts and techniques Understanding of SAP BW on HANA integration Ability to design and implement data extraction processes Expertise in data loading and transformation in SAP BW Proficiency in data integration using SAP BW Experience in data analysis with SAP BW on HANA Understanding of reporting capabilities in SAP BW

SAP BW On HANA Test Online Test

Q: What topics are covered in the SAP BW On HANA Test Online Test?

SAP BW HANA Data Modeling ETL processes Reporting Data Extraction Data Loading Data Transformation Data Integration Data Analysis

About the test:

The SAP BW On HANA Test evaluates a candidate's proficiency in SAP BW (Business Warehouse) and HANA for data modeling, ETL processes, reporting, data extraction, loading, transformation, integration, and analysis.

Covered skills:

SAP BW
Data Modeling
Reporting
Data Loading
Data Integration

HANA
ETL processes
Data Extraction
Data Transformation
Data Analysis

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9 reasons why

Adaface SAP BW On HANA Test Test is the most accurate way to shortlist SAP BW/4HANA Application Developers

Reason #1

Tests for on-the-job skills

The SAP BW On HANA Test Online Test helps recruiters and hiring managers identify qualified candidates from a pool of resumes, and helps in taking objective hiring decisions. It reduces the administrative overhead of interviewing too many candidates and saves time by filtering out unqualified candidates at the first step of the hiring process.

The test screens for the following skills that hiring managers look for in candidates:

Able to design and implement SAP BW solutions
Proficient in using SAP HANA for data modeling and analysis
Skilled in ETL processes for data extraction, loading, and transformation
Capable of integrating data from multiple sources into a unified system
Ability to analyze and report on data insights
Strong understanding of data integration and transformation
Excellent knowledge of SAP BW and HANA best practices
Effective problem-solving skills in SAP BW and HANA environments
Ability to optimize data loading and transformation processes
Proficient in data analysis using SAP BW and HANA tools

Reason #2

No trick questions

Traditional assessment tools use trick questions and puzzles for the screening, which creates a lot of frustration among candidates about having to go through irrelevant screening assessments.

View sample questions

The main reason we started Adaface is that traditional pre-employment assessment platforms are not a fair way for companies to evaluate candidates. At Adaface, our mission is to help companies find great candidates by assessing on-the-job skills required for a role.

Why we started Adaface

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Reason #3

Non-googleable questions

We have a very high focus on the quality of questions that test for on-the-job skills. Every question is non-googleable and we have a very high bar for the level of subject matter experts we onboard to create these questions. We have crawlers to check if any of the questions are leaked online. If/ when a question gets leaked, we get an alert. We change the question for you & let you know.

How we design questions

These are just a small sample from our library of 10,000+ questions. The actual questions on this SAP BW On HANA Test will be non-googleable.

🧐 Question
Medium Data Merging Data Merging Conditional Logic	Try practice test
A data engineer is tasked with merging and transforming data from two sources for a business analytics report. Source 1 is a SQL database 'Employee' with fields EmployeeID (int), Name (varchar), DepartmentID (int), and JoinDate (date). Source 2 is a CSV file 'Department' with fields DepartmentID (int), DepartmentName (varchar), and Budget (float). The objective is to create a summary table that lists EmployeeID, Name, DepartmentName, and YearsInCompany. The YearsInCompany should be calculated based on the JoinDate and the current date, rounded down to the nearest whole number. Consider the following initial SQL query: Which of the following modifications ensures accurate data transformation as per the requirements? A: Change FLOOR to CEILING in the calculation of YearsInCompany. B: Add WHERE e.JoinDate IS NOT NULL before the JOIN clause. C: Replace JOIN with LEFT JOIN and use COALESCE(d.DepartmentName, 'Unknown'). D: Change the YearsInCompany calculation to YEAR(CURRENT_DATE) - YEAR(e.JoinDate). E: Use DATEDIFF(YEAR, e.JoinDate, CURRENT_DATE) for YearsInCompany calculation.
Medium Data Updates Staging Data Warehouse	Try practice test
Jaylo is hired as Data warehouse engineer at Affflex Inc. Jaylo is tasked with designing an ETL process for loading data from SQL server database into a large fact table. Here are the specifications of the system: 1. Orders data from SQL to be stored in fact table in the warehouse each day with prior day’s order data 2. Loading new data must take as less time as possible 3. Remove data that is more then 2 years old 4. Ensure the data loads correctly 5. Minimize record locking and impact on transaction log Which of the following should be part of Jaylo’s ETL design? A: Partition the destination fact table by date B: Partition the destination fact table by customer C: Insert new data directly into fact table D: Delete old data directly from fact table E: Use partition switching and staging table to load new data F: Use partition switching and staging table to remove old data
Medium SQL in ETL Process SQL Code Interpretation Data Transformation SQL Functions	Try practice test
In an ETL process designed for a retail company, a complex SQL transformation is applied to the 'Sales' table. The 'Sales' table has fields SaleID, ProductID, Quantity, SaleDate, and Price. The goal is to generate a report that shows the total sales amount and average sale amount per product, aggregated monthly. The following SQL code snippet is used in the transformation step: What specific function does this SQL code perform in the context of the ETL process, and how does it contribute to the reporting goal? A: The code calculates the total and average sales amount for each product annually. B: It aggregates sales data by month and product, computing total and average sales amounts. C: This query generates a daily breakdown of sales, both total and average, for each product. D: The code is designed to identify the best-selling products on a monthly basis by sales amount. E: It calculates the overall sales and average price per product, without considering the time dimension.
Medium Trade Index Index	Try practice test
Silverman Sachs is a trading firm and deals with daily trade data for various stocks. They have the following fact table in their data warehouse: Table: Trades Indexes: None Columns: TradeID, TradeDate, Open, Close, High, Low, Volume Here are three common queries that are run on the data: Dhavid Polomon is hired as an ETL Developer and is tasked with implementing an indexing strategy for the Trades fact table. Here are the specifications of the indexing strategy: - All three common queries must use a columnstore index - Minimize number of indexes - Minimize size of indexes Which of the following strategies should Dhavid pick: A: Create three columnstore indexes: 1. Containing TradeDate and Close 2. Containing TradeDate, High and Low 3. Container TradeDate and Volume B: Create two columnstore indexes: 1. Containing TradeID, TradeDate, Volume and Close 2. Containing TradeID, TradeDate, High and Low C: Create one columnstore index that contains TradeDate, Close, High, Low and Volume D: Create one columnstore index that contains TradeID, Close, High, Low, Volume and Trade Date

	🧐 Question	🔧 Skill
	Medium Data Merging Data Merging Conditional Logic	2 mins ETL	Try practice test
A data engineer is tasked with merging and transforming data from two sources for a business analytics report. Source 1 is a SQL database 'Employee' with fields EmployeeID (int), Name (varchar), DepartmentID (int), and JoinDate (date). Source 2 is a CSV file 'Department' with fields DepartmentID (int), DepartmentName (varchar), and Budget (float). The objective is to create a summary table that lists EmployeeID, Name, DepartmentName, and YearsInCompany. The YearsInCompany should be calculated based on the JoinDate and the current date, rounded down to the nearest whole number. Consider the following initial SQL query: Which of the following modifications ensures accurate data transformation as per the requirements? A: Change FLOOR to CEILING in the calculation of YearsInCompany. B: Add WHERE e.JoinDate IS NOT NULL before the JOIN clause. C: Replace JOIN with LEFT JOIN and use COALESCE(d.DepartmentName, 'Unknown'). D: Change the YearsInCompany calculation to YEAR(CURRENT_DATE) - YEAR(e.JoinDate). E: Use DATEDIFF(YEAR, e.JoinDate, CURRENT_DATE) for YearsInCompany calculation.
	Medium Data Updates Staging Data Warehouse	2 mins ETL	Try practice test
Jaylo is hired as Data warehouse engineer at Affflex Inc. Jaylo is tasked with designing an ETL process for loading data from SQL server database into a large fact table. Here are the specifications of the system: 1. Orders data from SQL to be stored in fact table in the warehouse each day with prior day’s order data 2. Loading new data must take as less time as possible 3. Remove data that is more then 2 years old 4. Ensure the data loads correctly 5. Minimize record locking and impact on transaction log Which of the following should be part of Jaylo’s ETL design? A: Partition the destination fact table by date B: Partition the destination fact table by customer C: Insert new data directly into fact table D: Delete old data directly from fact table E: Use partition switching and staging table to load new data F: Use partition switching and staging table to remove old data
	Medium SQL in ETL Process SQL Code Interpretation Data Transformation SQL Functions	3 mins ETL	Try practice test
In an ETL process designed for a retail company, a complex SQL transformation is applied to the 'Sales' table. The 'Sales' table has fields SaleID, ProductID, Quantity, SaleDate, and Price. The goal is to generate a report that shows the total sales amount and average sale amount per product, aggregated monthly. The following SQL code snippet is used in the transformation step: What specific function does this SQL code perform in the context of the ETL process, and how does it contribute to the reporting goal? A: The code calculates the total and average sales amount for each product annually. B: It aggregates sales data by month and product, computing total and average sales amounts. C: This query generates a daily breakdown of sales, both total and average, for each product. D: The code is designed to identify the best-selling products on a monthly basis by sales amount. E: It calculates the overall sales and average price per product, without considering the time dimension.
	Medium Trade Index Index	3 mins ETL	Try practice test
Silverman Sachs is a trading firm and deals with daily trade data for various stocks. They have the following fact table in their data warehouse: Table: Trades Indexes: None Columns: TradeID, TradeDate, Open, Close, High, Low, Volume Here are three common queries that are run on the data: Dhavid Polomon is hired as an ETL Developer and is tasked with implementing an indexing strategy for the Trades fact table. Here are the specifications of the indexing strategy: - All three common queries must use a columnstore index - Minimize number of indexes - Minimize size of indexes Which of the following strategies should Dhavid pick: A: Create three columnstore indexes: 1. Containing TradeDate and Close 2. Containing TradeDate, High and Low 3. Container TradeDate and Volume B: Create two columnstore indexes: 1. Containing TradeID, TradeDate, Volume and Close 2. Containing TradeID, TradeDate, High and Low C: Create one columnstore index that contains TradeDate, Close, High, Low and Volume D: Create one columnstore index that contains TradeID, Close, High, Low, Volume and Trade Date

	🧐 Question	🔧 Skill	💪 Difficulty	⌛ Time
	Data Merging Data Merging Conditional Logic	ETL	Medium	2 mins	Try practice test
A data engineer is tasked with merging and transforming data from two sources for a business analytics report. Source 1 is a SQL database 'Employee' with fields EmployeeID (int), Name (varchar), DepartmentID (int), and JoinDate (date). Source 2 is a CSV file 'Department' with fields DepartmentID (int), DepartmentName (varchar), and Budget (float). The objective is to create a summary table that lists EmployeeID, Name, DepartmentName, and YearsInCompany. The YearsInCompany should be calculated based on the JoinDate and the current date, rounded down to the nearest whole number. Consider the following initial SQL query: Which of the following modifications ensures accurate data transformation as per the requirements? A: Change FLOOR to CEILING in the calculation of YearsInCompany. B: Add WHERE e.JoinDate IS NOT NULL before the JOIN clause. C: Replace JOIN with LEFT JOIN and use COALESCE(d.DepartmentName, 'Unknown'). D: Change the YearsInCompany calculation to YEAR(CURRENT_DATE) - YEAR(e.JoinDate). E: Use DATEDIFF(YEAR, e.JoinDate, CURRENT_DATE) for YearsInCompany calculation.
	Data Updates Staging Data Warehouse	ETL	Medium	2 mins	Try practice test
Jaylo is hired as Data warehouse engineer at Affflex Inc. Jaylo is tasked with designing an ETL process for loading data from SQL server database into a large fact table. Here are the specifications of the system: 1. Orders data from SQL to be stored in fact table in the warehouse each day with prior day’s order data 2. Loading new data must take as less time as possible 3. Remove data that is more then 2 years old 4. Ensure the data loads correctly 5. Minimize record locking and impact on transaction log Which of the following should be part of Jaylo’s ETL design? A: Partition the destination fact table by date B: Partition the destination fact table by customer C: Insert new data directly into fact table D: Delete old data directly from fact table E: Use partition switching and staging table to load new data F: Use partition switching and staging table to remove old data
	SQL in ETL Process SQL Code Interpretation Data Transformation SQL Functions	ETL	Medium	3 mins	Try practice test
In an ETL process designed for a retail company, a complex SQL transformation is applied to the 'Sales' table. The 'Sales' table has fields SaleID, ProductID, Quantity, SaleDate, and Price. The goal is to generate a report that shows the total sales amount and average sale amount per product, aggregated monthly. The following SQL code snippet is used in the transformation step: What specific function does this SQL code perform in the context of the ETL process, and how does it contribute to the reporting goal? A: The code calculates the total and average sales amount for each product annually. B: It aggregates sales data by month and product, computing total and average sales amounts. C: This query generates a daily breakdown of sales, both total and average, for each product. D: The code is designed to identify the best-selling products on a monthly basis by sales amount. E: It calculates the overall sales and average price per product, without considering the time dimension.
	Trade Index Index	ETL	Medium	3 mins	Try practice test
Silverman Sachs is a trading firm and deals with daily trade data for various stocks. They have the following fact table in their data warehouse: Table: Trades Indexes: None Columns: TradeID, TradeDate, Open, Close, High, Low, Volume Here are three common queries that are run on the data: Dhavid Polomon is hired as an ETL Developer and is tasked with implementing an indexing strategy for the Trades fact table. Here are the specifications of the indexing strategy: - All three common queries must use a columnstore index - Minimize number of indexes - Minimize size of indexes Which of the following strategies should Dhavid pick: A: Create three columnstore indexes: 1. Containing TradeDate and Close 2. Containing TradeDate, High and Low 3. Container TradeDate and Volume B: Create two columnstore indexes: 1. Containing TradeID, TradeDate, Volume and Close 2. Containing TradeID, TradeDate, High and Low C: Create one columnstore index that contains TradeDate, Close, High, Low and Volume D: Create one columnstore index that contains TradeID, Close, High, Low, Volume and Trade Date

Reason #4

1200+ customers in 75 countries

With Adaface, we were able to optimise our initial screening process by upwards of 75%, freeing up precious time for both hiring managers and our talent acquisition team alike!

Brandon Lee, Head of People, Love, Bonito

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Reason #5

Designed for elimination, not selection

The most important thing while implementing the pre-employment SAP BW On HANA Test in your hiring process is that it is an elimination tool, not a selection tool. In other words: you want to use the test to eliminate the candidates who do poorly on the test, not to select the candidates who come out at the top. While they are super valuable, pre-employment tests do not paint the entire picture of a candidate’s abilities, knowledge, and motivations. Multiple easy questions are more predictive of a candidate's ability than fewer hard questions. Harder questions are often "trick" based questions, which do not provide any meaningful signal about the candidate's skillset.

Science behind Adaface tests

Reason #6

1 click candidate invites

Email invites: You can send candidates an email invite to the SAP BW On HANA Test from your dashboard by entering their email address.

Public link: You can create a public link for each test that you can share with candidates.

API or integrations: You can invite candidates directly from your ATS by using our pre-built integrations with popular ATS systems or building a custom integration with your in-house ATS.

Reason #7

Detailed scorecards & benchmarks

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Reason #8

High completion rate

Adaface tests are conversational, low-stress, and take just 25-40 mins to complete.

This is why Adaface has the highest test-completion rate (86%), which is more than 2x better than traditional assessments.

Reason #9

Advanced Proctoring

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About the SAP BW On HANA Test Assessment Test

Why you should use Pre-employment SAP BW On HANA Test Online Test?

The SAP BW On HANA Test makes use of scenario-based questions to test for on-the-job skills as opposed to theoretical knowledge, ensuring that candidates who do well on this screening test have the relavant skills. The questions are designed to covered following on-the-job aspects:

Ability to perform data modeling in SAP BW
Proficiency in SAP HANA architecture and technology
Experience with ETL processes in SAP BW
Knowledge of data modeling concepts and techniques
Understanding of SAP BW on HANA integration
Ability to design and implement data extraction processes
Expertise in data loading and transformation in SAP BW
Proficiency in data integration using SAP BW
Experience in data analysis with SAP BW on HANA
Understanding of reporting capabilities in SAP BW

Once the test is sent to a candidate, the candidate receives a link in email to take the test. For each candidate, you will receive a detailed report with skills breakdown and benchmarks to shortlist the top candidates from your pool.

What topics are covered in the SAP BW On HANA Test Online Test?

SAP BW:
SAP BW (Business Warehouse) is a software product that enables businesses to analyze and report on large volumes of data. It is used for data modeling, data extraction, and data loading, allowing companies to transform raw data into meaningful insights for decision-making.
HANA:
HANA (High-Performance Analytical Appliance) is an in-memory database management system developed by SAP. It provides real-time analytics and data processing capabilities, accelerating data retrieval and reducing the need for traditional disk-based storage. Measuring HANA skills in this test ensures that candidates can leverage the speed and efficiency of this technology in the context of SAP BW.
Data Modeling:
Data modeling involves designing the structure and relationships of a database or data warehouse. It helps organizations organize and understand their data, enabling effective data analysis and implementation of business rules. Assessing candidates' data modeling skills ensures they can create efficient and scalable data models for SAP BW on HANA.
ETL processes:
ETL (Extract, Transform, Load) processes are used to extract data from various sources, transform it into a consistent format, and load it into a target system such as a data warehouse. Measuring ETL skills in this test ensures candidates can effectively handle the end-to-end process of acquiring, cleaning, and integrating data into SAP BW on HANA.
Reporting:
Reporting involves generating meaningful insights and visualizations from data for decision-making purposes. SAP BW on HANA provides various reporting capabilities, including ad hoc reporting, multidimensional reporting, and dashboarding. Measuring candidates' reporting skills ensures they can design, develop, and deliver accurate and intuitive reports using the features and functionalities of SAP BW on HANA.
Data Extraction:
Data extraction refers to the process of retrieving relevant data from various sources, such as databases, APIs, or flat files. It is a crucial step in data integration and enables organizations to gather the necessary information for analysis. Assessing candidates' data extraction skills ensures they can efficiently extract data from different sources and load it into SAP BW on HANA for further processing.
Data Loading:
Data loading involves transferring data from external sources into a target system, such as a data warehouse. It includes processes like data validation, transformation, and integration to ensure the quality and accuracy of the loaded data. Evaluating candidates' data loading skills ensures they can effectively handle the transfer and integration of data into SAP BW on HANA while maintaining data integrity and consistency.
Data Transformation:
Data transformation refers to the process of converting and manipulating data to meet specific requirements for analysis and reporting. It involves tasks like data cleansing, aggregation, and enrichment. Testing candidates' data transformation skills ensures they can perform complex data transformations within SAP BW on HANA to generate reliable and meaningful insights.
Data Integration:
Data integration involves combining data from various sources into a unified view or representation. It ensures data consistency and provides a holistic understanding of the organization's data assets. Measuring candidates' data integration skills in this test ensures they can seamlessly integrate data from different systems into SAP BW on HANA, enabling comprehensive data analysis and reporting.
Data Analysis:
Data analysis involves exploring, interpreting, and deriving insights from data to support decision-making. It includes techniques like statistical analysis, data mining, and predictive modeling. Evaluating candidates' data analysis skills ensures they can apply appropriate analytical techniques and tools within SAP BW on HANA to derive valuable business insights.
Full list of covered topics
The actual topics of the questions in the final test will depend on your job description and requirements. However, here's a list of topics you can expect the questions for SAP BW On HANA Test to be based on.
SAP BW
HANA
Data modeling
ETL processes
Reporting
Data extraction
Data loading
Data transformation
Data integration
Data analysis
SAP BW architecture
HANA modeling techniques
Creating BW objects
Data extraction techniques
Data loading best practices
ETL tools and methodologies
Reporting tools in SAP BW
Analyzing data in HANA
Data transformation functions
Data integration approaches
Performance optimization in SAP BW
HANA data modeling
Data extraction from SAP systems
Loading data from different sources
Transforming data using ETL processes
Data analysis techniques in BW
SAP HANA data types
Advanced reporting in SAP BW
Data replication in HANA
Loading data into HANA
Enhancing data quality in BW
Data integration challenges
Security and authorization in HANA
Dimensional modeling in BW
Data extraction from non-SAP systems
Data loading performance tuning
Master data management in SAP BW
HANA native development
SAP BW on HANA migration
Data transformation with ABAP
Data analysis using HANA views
Real-time data replication
Process chains in SAP BW
SAP HANA spatial modeling
Transaction data loading in BW
Delta extraction techniques
Data migration to HANA
Data modeling in BEx
Data modeling best practices
Analytical privileges in HANA
Data analysis using BW query designer
SAP BW and HANA security
ETL process automation
Performance optimization in HANA
Data load monitoring in BW
Nested queries in HANA
InfoProviders in SAP BW
Data archiving in BW

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What roles can I use the SAP BW On HANA Test Online Test for?

SAP BW/4HANA Application Developer
SAP BW Hana Lead
SAP – BW/BI Consultant on HANA
SAP BI/BW Consultant
SAP BI HANA Consultant

How is the SAP BW On HANA Test Online Test customized for senior candidates?

For intermediate/ experienced candidates, we customize the assessment questions to include advanced topics and increase the difficulty level of the questions. This might include adding questions on topics like

Ability to optimize data extraction and loading performance
Expertise in designing efficient data models in SAP BW
Knowledge of SAP HANA performance optimization techniques
Understanding of data transformation using SAP BW
Experience with data loading from various data sources
Proficiency in data governance and data quality
Ability to troubleshoot and debug SAP BW on HANA issues
Knowledge of SAP HANA security and authorization
Understanding of data replication and distribution in SAP HANA
Experience in data analysis using SAP HANA

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The hiring managers felt that through the technical questions that they asked during the panel interviews, they were able to tell which candidates had better scores, and differentiated with those who did not score as well. They are highly satisfied with the quality of candidates shortlisted with the Adaface screening.

85%

reduction in screening time

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SAP BW On HANA Test Hiring Test FAQs

Can I combine multiple skills into one custom assessment?

Yes, absolutely. Custom assessments are set up based on your job description, and will include questions on all must-have skills you specify. Here's a quick guide on how you can request a custom test.

Do you have any anti-cheating or proctoring features in place?

We have the following anti-cheating features in place:

Non-googleable questions
IP proctoring
Screen proctoring
Web proctoring
Webcam proctoring
Plagiarism detection
Secure browser
Copy paste protection

Read more about the proctoring features.

How do I interpret test scores?

The primary thing to keep in mind is that an assessment is an elimination tool, not a selection tool. A skills assessment is optimized to help you eliminate candidates who are not technically qualified for the role, it is not optimized to help you find the best candidate for the role. So the ideal way to use an assessment is to decide a threshold score (typically 55%, we help you benchmark) and invite all candidates who score above the threshold for the next rounds of interview.

What experience level can I use this test for?

Each Adaface assessment is customized to your job description/ ideal candidate persona (our subject matter experts will pick the right questions for your assessment from our library of 10000+ questions). This assessment can be customized for any experience level.

Does every candidate get the same questions?

Yes, it makes it much easier for you to compare candidates. Options for MCQ questions and the order of questions are randomized. We have anti-cheating/ proctoring features in place. In our enterprise plan, we also have the option to create multiple versions of the same assessment with questions of similar difficulty levels.