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

The SAP BW op 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: Mogelijkheid om gegevensmodellering uit te voeren in SAP BW Vaardigheid in SAP HANA -architectuur en technologie Ervaring met ETL -processen in SAP BW Kennis van concepten en technieken voor gegevensmodellering Inzicht in SAP BW over HANA -integratie Mogelijkheid om gegevensextractieprocessen te ontwerpen en te implementeren Expertise in het laden en transformeren van gegevens in SAP BW Vaardigheid in gegevensintegratie met SAP BW Ervaring met gegevensanalyse met SAP BW op HANA Inzicht in rapportagemogelijkheden in SAP BW

SAP BW On HANA Test Online Test

About the test:

De SAP BW op HANA -test evalueert de vaardigheid van een kandidaat in SAP BW (Business Warehouse) en HANA voor datamodellering, ETL -processen, rapportage, gegevensextractie, laden, transformatie, integratie en analyse.

Covered skills:

SAP BW
Datamodellering
Rapportage
Gegevens laden
Gegevens integratie

Hana
ETL -processen
Data-extractie
Gegevenstransformatie
Gegevensanalyse

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9 reasons why

Adaface SAP BW On HANA Test Test is the most accurate way to shortlist SAP BW/4HANA TOEPASSING 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:

In staat om SAP BW -oplossingen te ontwerpen en te implementeren
Bekwaam in het gebruik van SAP HANA voor gegevensmodellering en analyse
Bekwaam in ETL -processen voor gegevensextractie, laden en transformatie
In staat om gegevens uit meerdere bronnen te integreren in een uniform systeem
Mogelijkheid om gegevensinzichten te analyseren en te rapporteren
Sterk begrip van gegevensintegratie en transformatie
Uitstekende kennis van SAP BW en HANA Best Practices
Effectieve probleemoplossende vaardigheden in SAP BW- en HANA-omgevingen
Mogelijkheid om gegevenslasten en transformatieprocessen te optimaliseren
Bekwaam in gegevensanalyse met behulp van SAP BW- en 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

Dit zijn slechts een klein monster uit onze bibliotheek met meer dan 10.000 vragen. De werkelijke vragen hierover SAP BW op HANA -test zal niet-googelbaar zijn.

🧐 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

Met Adaface konden we ons eerste screeningproces met ruim 75% optimaliseren, waardoor kostbare tijd vrijkwam voor zowel de rekruteringsmanagers als ons talentacquisitieteam!

Brandon Lee, Hoofd Mensen, Love, Bonito

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Reason #5

Designed for elimination, not selection

The most important thing while implementing the pre-employment SAP BW op 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 op 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

Learn more

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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 op 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:

Mogelijkheid om gegevensmodellering uit te voeren in SAP BW
Vaardigheid in SAP HANA -architectuur en technologie
Ervaring met ETL -processen in SAP BW
Kennis van concepten en technieken voor gegevensmodellering
Inzicht in SAP BW over HANA -integratie
Mogelijkheid om gegevensextractieprocessen te ontwerpen en te implementeren
Expertise in het laden en transformeren van gegevens in SAP BW
Vaardigheid in gegevensintegratie met SAP BW
Ervaring met gegevensanalyse met SAP BW op HANA
Inzicht in rapportagemogelijkheden 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?

HANA:
HANA (high-performance analytisch Appliance) is een in-memory databasebeheersysteem ontwikkeld door SAP. Het biedt realtime analyses en gegevensverwerkingsmogelijkheden, het versnellen van gegevens ophalen en het verminderen van de behoefte aan traditionele opslaggebaseerde opslag. Het meten van HANA -vaardigheden in deze test zorgt ervoor dat kandidaten de snelheid en efficiëntie van deze technologie kunnen benutten in de context van SAP BW.
Datamodellering:
Gegevensmodellering omvat het ontwerpen van de structuur en relaties van een database of datawarehouse. Het helpt organisaties hun gegevens te organiseren en te begrijpen, waardoor effectieve gegevensanalyse en implementatie van bedrijfsregels mogelijk worden gemaakt. Het beoordelen van de gegevensmodelleringsvaardigheden van kandidaten zorgt ervoor dat ze efficiënte en schaalbare datamodellen kunnen maken voor SAP BW op HANA.
ETL -processen:
ETL (extract, transformeren, laden) worden gebruikt Extraheer gegevens uit verschillende bronnen, transformeren deze in een consistent formaat en laad deze in een doelsysteem zoals een datawarehouse. Het meten van ETL-vaardigheden in deze test zorgt ervoor dat kandidaten effectief het end-to-end proces van het verwerven, reinigen en integreren van gegevens in SAP BW op HANA kunnen verwerken.
Rapportage:
Rapportage omvat betrokken het genereren van betekenisvolle inzichten en visualisaties uit gegevens voor besluitvorming. SAP BW op HANA biedt verschillende rapportagemogelijkheden, waaronder ad hoc rapportage, multidimensionale rapportage en dashboarding. Het meten van de rapportagevaardigheden van kandidaten zorgt ervoor dat ze nauwkeurige en intuïtieve rapporten kunnen ontwerpen, ontwikkelen en leveren Het proces van het ophalen van relevante gegevens uit verschillende bronnen, zoals databases, API's of platte bestanden. Het is een cruciale stap in gegevensintegratie en stelt organisaties in staat om de nodige informatie voor analyse te verzamelen. Het beoordelen van de gegevensextractievaardigheden van kandidaten zorgt ervoor dat ze gegevens efficiënt uit verschillende bronnen kunnen extraheren en deze in SAP BW op HANA kunnen laden voor verdere verwerking.
Gegevenslaading:
Gegevensbelasting omvat het overbrengen van gegevens uit Externe bronnen in een doelsysteem, zoals een datawarehouse. Het bevat processen zoals gegevensvalidatie, transformatie en integratie om de kwaliteit en nauwkeurigheid van de geladen gegevens te waarborgen. Het evalueren van de gegevenslaadvaardigheden van kandidaten zorgt ervoor dat ze de overdracht en integratie van gegevens in SAP BW op HANA effectief kunnen verwerken met behoud van gegevensintegriteit en consistentie.
Data -transformatie:
Data -transformatie verwijst naar Het proces van het converteren en manipuleren van gegevens om te voldoen aan specifieke vereisten voor analyse en rapportage. Het omvat taken zoals gegevensreiniging, aggregatie en verrijking. Het testen van de gegevenstransformatievaardigheden van kandidaten zorgt ervoor dat ze complexe gegevenstransformaties binnen SAP BW op HANA kunnen uitvoeren om betrouwbare en zinvolle inzichten te genereren.
Gegevensintegratie:
Gegevensintegratie omvat het combineren van gegevens uit verschillende bronnen in een uniforme visie of weergave. Het zorgt voor gegevensconsistentie en biedt een holistisch begrip van de gegevensactiva van de organisatie. Het meten van de gegevensintegratievaardigheden van de kandidaten in deze test zorgt ervoor dat ze gegevens naadloos kunnen integreren van verschillende systemen in SAP BW op HANA, waardoor uitgebreide gegevensanalyse en rapportage mogelijk worden. omvat het verkennen, interpreteren en afleiden van inzichten uit gegevens om de besluitvorming te ondersteunen. Het omvat technieken zoals statistische analyse, datamining en voorspellende modellering. Het evalueren van de gegevensanalysevaardigheden van kandidaten zorgt ervoor dat ze geschikte analytische technieken en tools binnen SAP BW op HANA kunnen toepassen om waardevolle zakelijke inzichten af te leiden.
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 op HANA -test to be based on.
SAP BW
Hana
Datamodellering
ETL -processen
Rapportage
Data-extractie
Gegevens laden
Gegevenstransformatie
Gegevens integratie
Gegevensanalyse
SAP BW -architectuur
HANA -modelleringstechnieken
BW -objecten maken
Data -extractietechnieken
Gegevens laden best practices
ETL -tools en methoden
Rapportagetools in SAP BW
Gegevens analyseren in HANA
Gegevenstransformatie -functies
Gegevensintegratiebenaderingen
Prestatie -optimalisatie in SAP BW
HANA -datamodellering
Data -extractie van SAP -systemen
Gegevens uit verschillende bronnen laden
Gegevens transformeren met behulp van ETL -processen
Gegevensanalysetechnieken in BW
SAP HANA -gegevenstypen
Geavanceerde rapportage in SAP BW
Gegevensreplicatie in HANA
Gegevens laden in HANA
De gegevenskwaliteit verbeteren in BW
Gegevensintegratie -uitdagingen
Beveiliging en autorisatie in Hana
Dimensionale modellering in BW
Data-extractie uit niet-SAP-systemen
Gegevens laden prestatietuning
Master Data Management in SAP BW
HANA Native Development
SAP BW over HANA -migratie
Gegevenstransformatie met ABAP
Gegevensanalyse met HANA -weergaven
Realtime gegevensreplicatie
Procesketens in SAP BW
SAP HANA RIPATIALE MODELLING
Transactiegegevens laden in BW
Delta -extractietechnieken
Gegevensmigratie naar Hana
Gegevensmodellering in Bex
Gegevensmodellering best practices
Analytische privileges in Hana
Gegevensanalyse met BW Query Designer
SAP BW en HANA BEVEILING
ETL -procesautomatisering
Prestatie -optimalisatie in HANA
Gegevensladen Monitoring in BW
Geneste vragen in Hana
Infoproviders in SAP BW
Data -archivering in BW

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

SAP BW/4HANA TOEPASSING Developer
SAP BW HANA LOD
SAP - BW/BI -consultant op 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

Mogelijkheid om gegevensextractie en laadprestaties te optimaliseren
Expertise in het ontwerpen van efficiënte gegevensmodellen in SAP BW
Kennis van SAP HANA -prestatie -optimalisatietechnieken
Inzicht in gegevenstransformatie met SAP BW
Ervaring met het laden van gegevens uit verschillende gegevensbronnen
Vaardigheid in gegevensbeheer en gegevenskwaliteit
Mogelijkheid om SAP BW op te lossen en op te lossen over HANA -problemen
Kennis van SAP HANA -beveiliging en autorisatie
Inzicht in gegevensreplicatie en distributie in SAP HANA
Ervaring met gegevensanalyse met SAP HANA

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De rekruteringsmanagers waren van mening dat ze door de technische vragen die ze tijdens de panelgesprekken stelden, konden zien welke kandidaten beter scoorden, en onderscheidden ze zich met degenen die niet zo goed scoorden. Zij zijn zeer tevreden met de kwaliteit van de kandidaten op de shortlist van de Adaface-screening.

85%

Vermindering van de screeningstijd

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SAP BW On HANA Test Hiring Test Veelgestelde vragen

Kan ik meerdere vaardigheden combineren in één aangepaste beoordeling?

Ja absoluut. Aangepaste beoordelingen zijn opgezet op basis van uw functiebeschrijving en bevatten vragen over alle must-have vaardigheden die u opgeeft.

Heeft u functies tegen latere of proctoring op hun plaats?

We hebben de volgende anti-cheating-functies op zijn plaats:

Niet-googelbare vragen
IP Proctoring
Web Proctoring
Webcam Proctoring
Plagiaatdetectie
Beveilig browser

Lees meer over de Proctoring -functies.

Hoe interpreteer ik testscores?

Het belangrijkste om in gedachten te houden is dat een beoordeling een eliminatietool is, geen selectietool. Een vaardighedenbeoordeling is geoptimaliseerd om u te helpen kandidaten te elimineren die niet technisch gekwalificeerd zijn voor de rol, het is niet geoptimaliseerd om u te helpen de beste kandidaat voor de rol te vinden. Dus de ideale manier om een beoordeling te gebruiken is om een drempelscore te bepalen (meestal 55%, wij helpen u benchmark) en alle kandidaten uit te nodigen die boven de drempel scoren voor de volgende interviewrondes.

Voor welk ervaringsniveau kan ik deze test gebruiken?

Elke ADAFACE -beoordeling is aangepast aan uw functiebeschrijving/ ideale kandidaatpersonage (onze experts van het onderwerp zullen de juiste vragen kiezen voor uw beoordeling uit onze bibliotheek van 10000+ vragen). Deze beoordeling kan worden aangepast voor elk ervaringsniveau.

Krijgt elke kandidaat dezelfde vragen?

Ja, het maakt het veel gemakkelijker voor u om kandidaten te vergelijken. Opties voor MCQ -vragen en de volgorde van vragen worden gerandomiseerd. We hebben anti-cheating/proctoring functies. In ons bedrijfsplan hebben we ook de optie om meerdere versies van dezelfde beoordeling te maken met vragen over vergelijkbare moeilijkheidsniveaus.