Why you should use Data Wrangling Test?

The Data kranglingstest 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: Datautvinning ved bruk av forskjellige metoder Data som analyserer med presisjon og nøyaktighet Dataintegrasjon for sømløs dataflyt Kvalitetsvurdering for å sikre dataintegritet Datavalidering for å identifisere og rette feil Datamodellering for effektiv representasjon Datatolkning for å utlede innsikt Dataanalyse ved bruk av statistiske teknikker Håndtering av unntak og feil i datamanipulering Effektivt administrere store datasett

Data Wrangling Test

Q: What topics are covered in the Data Wrangling Test?

Datautvinning Data -parsing Dataintegrasjon Kvalitetsvurdering Datavalidering Datamodellering Datatolkning Dataanalyse

About the test:

Data -kranglingstesten evaluerer en kandidats ferdigheter i rengjøring, transformering og organisering av rå data til et strukturert format som er egnet for analyse. Den tester deres forståelse av datamodellering, tolkning, analyse og inngangsprosesser.

Covered skills:

Datautvinning
Dataintegrasjon
Datavalidering
Datatolkning

Data -parsing
Kvalitetsvurdering
Datamodellering
Dataanalyse

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9 reasons why

Adaface Data Wrangling Assessment Test is the most accurate way to shortlist Data analytikers

Reason #1

Tests for on-the-job skills

The Data Wrangling 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:

Evne til å hente ut data fra forskjellige kilder
Evne til å analysere og rengjøre data
Evne til å integrere og kombinere data fra flere kilder
Evne til å vurdere kvaliteten på data
Evne til å validere data og identifisere eventuelle uoverensstemmelser
Evne til å lage datamodeller
Evne til å tolke data og trekke meningsfulle konklusjoner
Evne til å analysere data ved hjelp av statistiske metoder og verktøy

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

Dette er bare en liten prøve fra biblioteket vårt med 10.000+ spørsmål. De faktiske spørsmålene om dette Data kranglingstest vil være ikke-googlable.

🧐 Question
Easy Healthcare System Data Integrity Normalization Referential Integrity	Try practice test
You are designing a data model for a healthcare system with the following requirements: A: A separate table for each entity with foreign keys as specified, and a DoctorPatient table linking Doctors to Patients. B: A separate table for each entity with foreign keys as specified, without additional tables. C: A combined PatientDoctor table replacing Patient and Doctor, and separate tables for Appointment and Prescription. D: A separate table for each entity with foreign keys, and a PatientPrescription table to track prescriptions directly linked to patients. E: A single table combining Patient, Doctor, Appointment, and Prescription into one. F: A separate table for each entity with foreign keys as specified, and an AppointmentDetails table linking Appointments to Prescriptions.
Hard ER Diagram and minimum tables ER Diagram	Try practice test
Look at the given ER diagram. What do you think is the least number of tables we would need to represent M, N, P, R1 and R2?
Medium Normalization Process Normalization Database Design Anomaly Elimination	Try practice test
Consider a healthcare database with a table named PatientRecords that stores patient visit information. The table has the following attributes: - VisitID - PatientID - PatientName - DoctorID - DoctorName - VisitDate - Diagnosis - Treatment - TreatmentCost In this table: - Each VisitID uniquely identifies a patient's visit and is associated with one PatientID. - PatientID is associated with exactly one PatientName. - Each DoctorID is associated with a unique DoctorName. - TreatmentCost is a fixed cost based on the Treatment. Evaluating the PatientRecords table, which of the following statements most accurately describes its normalization state and the required actions for higher normalization? A: The table is in 1NF. To achieve 2NF, remove partial dependencies by separating Patient information (PatientID, PatientName) and Doctor information (DoctorID, DoctorName) into different tables. B: The table is in 2NF. To achieve 3NF, remove transitive dependencies by creating separate tables for Patients (PatientID, PatientName), Doctors (DoctorID, DoctorName), and Visits (VisitID, PatientID, DoctorID, VisitDate, Diagnosis, Treatment, TreatmentCost). C: The table is in 3NF. To achieve BCNF, adjust for functional dependencies such as moving DoctorName to a separate Doctors table. D: The table is in 1NF. To achieve 3NF, create separate tables for Patients, Doctors, and Visits, and remove TreatmentCost as it is a derived attribute. E: The table is in 2NF. To achieve 4NF, address any multi-valued dependencies by separating Visit details and Treatment details. F: The table is in 3NF. To achieve 4NF, remove multi-valued dependencies related to VisitID.
Medium University Courses ER Diagrams Complex Relationships Integrity Constraints	Try practice test
Based on the ER diagram, which of the following statements is accurate and requires specific knowledge of the ER diagram's details? A: A Student can major in multiple Departments. B: An Instructor can belong to multiple Departments. C: A Course can be offered by multiple Departments. D: Enrollment records can link a Student to multiple Courses in a single semester. E: Each Course must be associated with an Enrollment record. F: A Department can offer courses without having any instructors.
Medium Dividends Financial Analysis Percentage and Average Calculations	Try practice test
Consider the following line chart which shows the money invested by a company in production each year and the sales made by the company each year. If the pie chart shows the shareholding pattern of the company and the company gives 10% of the profit as dividends to its share holders then what is the average dividend received by retail investors from 2000 to 2004?
Medium Laptop Brands Proportions and Percentages Financial Reasoning	Try practice test
Given below is the list of laptop brands and their details in which some data is missing. If the cost price of Dell is 3/5 of the cost price of Lenovo, then what will be the %profit of Dell?
Hard Median Trend Analysis Statistical Reasoning	Try practice test
Consider the following line chart which shows the sales of five different companies from 2000 to 2009. Which of the following companies has the maximum percentage increase in the median from 2000 to 2004 and 2005 to 2009.
Medium Hiring Developer Skewed Data Graph	Try practice test
Two companies A and B hired developers from the year 2001 to 2005. The given bar graph shows the hiring details. Now select the statements that are true based on the given details. A: The data given for Company A is skewed to the left. B: The data given for Company B is skewed to the right. C: The data given for Company A is skewed to the right. D: For Company B, mean and mode are equal. E: For Company B, mean is equal to median but less than mode. F: For Company A, median is less than mode but greater than mean.
Medium Negative correlation	Try practice test
Saffi, one of the popular schools in San Francisco did a school wide study of the students in middle school. The study found that there is a negative correlation between the time spent on Facebook per day by students and their academic achievement. How can we understand the results of this study? A: An increase in time spent on Facebook per day causes a drop in the academic achievement of students at the middle school level. B: There is an association between an increase in time spent on Facebook per day and the drop in the academic achievement of students at Saffi. C: An increase in the time spent on Facebook per day causes a drop in the academic achievement of students at Saffi. D: There is an association between an increase in time spent on Facebook per day and the drop in the academic achievement of students at the middle school level.

	🧐 Question	🔧 Skill
	Easy Healthcare System Data Integrity Normalization Referential Integrity	2 mins Data Modeling	Try practice test
You are designing a data model for a healthcare system with the following requirements: A: A separate table for each entity with foreign keys as specified, and a DoctorPatient table linking Doctors to Patients. B: A separate table for each entity with foreign keys as specified, without additional tables. C: A combined PatientDoctor table replacing Patient and Doctor, and separate tables for Appointment and Prescription. D: A separate table for each entity with foreign keys, and a PatientPrescription table to track prescriptions directly linked to patients. E: A single table combining Patient, Doctor, Appointment, and Prescription into one. F: A separate table for each entity with foreign keys as specified, and an AppointmentDetails table linking Appointments to Prescriptions.
	Hard ER Diagram and minimum tables ER Diagram	2 mins Data Modeling	Try practice test
Look at the given ER diagram. What do you think is the least number of tables we would need to represent M, N, P, R1 and R2?
	Medium Normalization Process Normalization Database Design Anomaly Elimination	3 mins Data Modeling	Try practice test
Consider a healthcare database with a table named PatientRecords that stores patient visit information. The table has the following attributes: - VisitID - PatientID - PatientName - DoctorID - DoctorName - VisitDate - Diagnosis - Treatment - TreatmentCost In this table: - Each VisitID uniquely identifies a patient's visit and is associated with one PatientID. - PatientID is associated with exactly one PatientName. - Each DoctorID is associated with a unique DoctorName. - TreatmentCost is a fixed cost based on the Treatment. Evaluating the PatientRecords table, which of the following statements most accurately describes its normalization state and the required actions for higher normalization? A: The table is in 1NF. To achieve 2NF, remove partial dependencies by separating Patient information (PatientID, PatientName) and Doctor information (DoctorID, DoctorName) into different tables. B: The table is in 2NF. To achieve 3NF, remove transitive dependencies by creating separate tables for Patients (PatientID, PatientName), Doctors (DoctorID, DoctorName), and Visits (VisitID, PatientID, DoctorID, VisitDate, Diagnosis, Treatment, TreatmentCost). C: The table is in 3NF. To achieve BCNF, adjust for functional dependencies such as moving DoctorName to a separate Doctors table. D: The table is in 1NF. To achieve 3NF, create separate tables for Patients, Doctors, and Visits, and remove TreatmentCost as it is a derived attribute. E: The table is in 2NF. To achieve 4NF, address any multi-valued dependencies by separating Visit details and Treatment details. F: The table is in 3NF. To achieve 4NF, remove multi-valued dependencies related to VisitID.
	Medium University Courses ER Diagrams Complex Relationships Integrity Constraints	2 mins Data Modeling	Try practice test
Based on the ER diagram, which of the following statements is accurate and requires specific knowledge of the ER diagram's details? A: A Student can major in multiple Departments. B: An Instructor can belong to multiple Departments. C: A Course can be offered by multiple Departments. D: Enrollment records can link a Student to multiple Courses in a single semester. E: Each Course must be associated with an Enrollment record. F: A Department can offer courses without having any instructors.
	Medium Dividends Financial Analysis Percentage and Average Calculations	3 mins Data Interpretation	Try practice test
Consider the following line chart which shows the money invested by a company in production each year and the sales made by the company each year. If the pie chart shows the shareholding pattern of the company and the company gives 10% of the profit as dividends to its share holders then what is the average dividend received by retail investors from 2000 to 2004?
	Medium Laptop Brands Proportions and Percentages Financial Reasoning	2 mins Data Interpretation	Try practice test
Given below is the list of laptop brands and their details in which some data is missing. If the cost price of Dell is 3/5 of the cost price of Lenovo, then what will be the %profit of Dell?
	Hard Median Trend Analysis Statistical Reasoning	3 mins Data Interpretation	Try practice test
Consider the following line chart which shows the sales of five different companies from 2000 to 2009. Which of the following companies has the maximum percentage increase in the median from 2000 to 2004 and 2005 to 2009.
	Medium Hiring Developer Skewed Data Graph	3 mins Data Analysis	Try practice test
Two companies A and B hired developers from the year 2001 to 2005. The given bar graph shows the hiring details. Now select the statements that are true based on the given details. A: The data given for Company A is skewed to the left. B: The data given for Company B is skewed to the right. C: The data given for Company A is skewed to the right. D: For Company B, mean and mode are equal. E: For Company B, mean is equal to median but less than mode. F: For Company A, median is less than mode but greater than mean.
	Medium Negative correlation	2 mins Data Analysis	Try practice test
Saffi, one of the popular schools in San Francisco did a school wide study of the students in middle school. The study found that there is a negative correlation between the time spent on Facebook per day by students and their academic achievement. How can we understand the results of this study? A: An increase in time spent on Facebook per day causes a drop in the academic achievement of students at the middle school level. B: There is an association between an increase in time spent on Facebook per day and the drop in the academic achievement of students at Saffi. C: An increase in the time spent on Facebook per day causes a drop in the academic achievement of students at Saffi. D: There is an association between an increase in time spent on Facebook per day and the drop in the academic achievement of students at the middle school level.

	🧐 Question	🔧 Skill	💪 Difficulty	⌛ Time
	Healthcare System Data Integrity Normalization Referential Integrity	Data Modeling	Easy	2 mins	Try practice test
You are designing a data model for a healthcare system with the following requirements: A: A separate table for each entity with foreign keys as specified, and a DoctorPatient table linking Doctors to Patients. B: A separate table for each entity with foreign keys as specified, without additional tables. C: A combined PatientDoctor table replacing Patient and Doctor, and separate tables for Appointment and Prescription. D: A separate table for each entity with foreign keys, and a PatientPrescription table to track prescriptions directly linked to patients. E: A single table combining Patient, Doctor, Appointment, and Prescription into one. F: A separate table for each entity with foreign keys as specified, and an AppointmentDetails table linking Appointments to Prescriptions.
	ER Diagram and minimum tables ER Diagram	Data Modeling	Hard	2 mins	Try practice test
Look at the given ER diagram. What do you think is the least number of tables we would need to represent M, N, P, R1 and R2?
	Normalization Process Normalization Database Design Anomaly Elimination	Data Modeling	Medium	3 mins	Try practice test
Consider a healthcare database with a table named PatientRecords that stores patient visit information. The table has the following attributes: - VisitID - PatientID - PatientName - DoctorID - DoctorName - VisitDate - Diagnosis - Treatment - TreatmentCost In this table: - Each VisitID uniquely identifies a patient's visit and is associated with one PatientID. - PatientID is associated with exactly one PatientName. - Each DoctorID is associated with a unique DoctorName. - TreatmentCost is a fixed cost based on the Treatment. Evaluating the PatientRecords table, which of the following statements most accurately describes its normalization state and the required actions for higher normalization? A: The table is in 1NF. To achieve 2NF, remove partial dependencies by separating Patient information (PatientID, PatientName) and Doctor information (DoctorID, DoctorName) into different tables. B: The table is in 2NF. To achieve 3NF, remove transitive dependencies by creating separate tables for Patients (PatientID, PatientName), Doctors (DoctorID, DoctorName), and Visits (VisitID, PatientID, DoctorID, VisitDate, Diagnosis, Treatment, TreatmentCost). C: The table is in 3NF. To achieve BCNF, adjust for functional dependencies such as moving DoctorName to a separate Doctors table. D: The table is in 1NF. To achieve 3NF, create separate tables for Patients, Doctors, and Visits, and remove TreatmentCost as it is a derived attribute. E: The table is in 2NF. To achieve 4NF, address any multi-valued dependencies by separating Visit details and Treatment details. F: The table is in 3NF. To achieve 4NF, remove multi-valued dependencies related to VisitID.
	University Courses ER Diagrams Complex Relationships Integrity Constraints	Data Modeling	Medium	2 mins	Try practice test
Based on the ER diagram, which of the following statements is accurate and requires specific knowledge of the ER diagram's details? A: A Student can major in multiple Departments. B: An Instructor can belong to multiple Departments. C: A Course can be offered by multiple Departments. D: Enrollment records can link a Student to multiple Courses in a single semester. E: Each Course must be associated with an Enrollment record. F: A Department can offer courses without having any instructors.
	Dividends Financial Analysis Percentage and Average Calculations	Data Interpretation	Medium	3 mins	Try practice test
Consider the following line chart which shows the money invested by a company in production each year and the sales made by the company each year. If the pie chart shows the shareholding pattern of the company and the company gives 10% of the profit as dividends to its share holders then what is the average dividend received by retail investors from 2000 to 2004?
	Laptop Brands Proportions and Percentages Financial Reasoning	Data Interpretation	Medium	2 mins	Try practice test
Given below is the list of laptop brands and their details in which some data is missing. If the cost price of Dell is 3/5 of the cost price of Lenovo, then what will be the %profit of Dell?
	Median Trend Analysis Statistical Reasoning	Data Interpretation	Hard	3 mins	Try practice test
Consider the following line chart which shows the sales of five different companies from 2000 to 2009. Which of the following companies has the maximum percentage increase in the median from 2000 to 2004 and 2005 to 2009.
	Hiring Developer Skewed Data Graph	Data Analysis	Medium	3 mins	Try practice test
Two companies A and B hired developers from the year 2001 to 2005. The given bar graph shows the hiring details. Now select the statements that are true based on the given details. A: The data given for Company A is skewed to the left. B: The data given for Company B is skewed to the right. C: The data given for Company A is skewed to the right. D: For Company B, mean and mode are equal. E: For Company B, mean is equal to median but less than mode. F: For Company A, median is less than mode but greater than mean.
	Negative correlation	Data Analysis	Medium	2 mins	Try practice test
Saffi, one of the popular schools in San Francisco did a school wide study of the students in middle school. The study found that there is a negative correlation between the time spent on Facebook per day by students and their academic achievement. How can we understand the results of this study? A: An increase in time spent on Facebook per day causes a drop in the academic achievement of students at the middle school level. B: There is an association between an increase in time spent on Facebook per day and the drop in the academic achievement of students at Saffi. C: An increase in the time spent on Facebook per day causes a drop in the academic achievement of students at Saffi. D: There is an association between an increase in time spent on Facebook per day and the drop in the academic achievement of students at the middle school level.

Reason #4

1200+ customers in 75 countries

Med Adaface var vi i stand til å optimalisere den første screeningsprosessen vår med oppover 75 %, og frigjorde dyrebar tid for både ansettelsesledere og vårt talentanskaffelsesteam!

Brandon Lee, Leder for mennesker, Love, Bonito

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Reason #5

Designed for elimination, not selection

The most important thing while implementing the pre-employment Data kranglingstest 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 Data kranglingstest 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 Data Wrangling Online Test

Why you should use Pre-employment Data Wrangling Test?

The Data kranglingstest 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:

Datautvinning ved bruk av forskjellige metoder
Data som analyserer med presisjon og nøyaktighet
Dataintegrasjon for sømløs dataflyt
Kvalitetsvurdering for å sikre dataintegritet
Datavalidering for å identifisere og rette feil
Datamodellering for effektiv representasjon
Datatolkning for å utlede innsikt
Dataanalyse ved bruk av statistiske teknikker
Håndtering av unntak og feil i datamanipulering
Effektivt administrere store datasett

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 Data Wrangling Test?

Data-parsing
Data-parsing innebærer å bryte ned komplekse datastrukturer i mindre , meningsfulle komponenter. Det er avgjørende å måle denne ferdigheten å evaluere kandidatens evne til å trekke ut spesifikk informasjon og manipulere data for videre behandling.
Dataintegrasjon
Dataintegrasjon refererer til å kombinere data fra forskjellige kilder til en enhetlig og konsistent format for analyse. Testing av denne ferdigheten hjelper til med å bestemme kandidatens ferdigheter i å slå sammen datasett og forberede dem på nøyaktig dataanalyse og rapportering.
Kvalitetsvurdering
Kvalitetsvurdering innebærer å evaluere påliteligheten, nøyaktigheten og fullstendigheten av data . Denne ferdigheten måles i testen for å vurdere kandidatens evne til å identifisere og rette opp eventuelle uoverensstemmelser, feil eller duplikasjoner i det innsamlede datasettet.
Datavalidering
Validering med data innebærer å verifisere integriteten og nøyaktighet av data ved å utføre valideringskontroller basert på definerte regler eller begrensninger. Å måle denne ferdigheten hjelper til med å evaluere kandidatens ferdigheter i å identifisere og løse datakvalitetsproblemer for å sikre datakonsistens og pålitelighet.
Datamodellering
Datamodellering innebærer å designe og konstruere en konseptuell representasjon av data For å støtte effektiv datahåndtering og analyse. Denne ferdigheten måles i testen for å vurdere kandidatens evne til å lage strukturerte datamodeller som muliggjør effektiv dataorganisasjon, lagring og gjenfinning.
Datatolkning
Datatolkning refererer til forståelsen og analyse av data for å utlede meningsfull innsikt og ta informerte beslutninger. Testing av denne ferdigheten hjelper til med å evaluere kandidatens evne til å tolke datavisualisering, statistisk analyse og andre teknikker for å trekke ut verdifull informasjon.
Dataanalyse
Dataanalyse innebærer å anvende statistiske og analysemetoder for å studere , transformere og evaluere data for å trekke konklusjoner og ta datadrevne beslutninger. Testing av denne ferdigheten hjelper til med å vurdere kandidatens ferdigheter i å bruke forskjellige teknikker og verktøy for å avdekke mønstre, trender, korrelasjoner og outliers i dataene.
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 Data kranglingstest to be based on.
Datautvinning
Nettskraping
API -integrasjon
Regex
Rengjøring av data
Datatransformasjon
Data sammenslåing
Data deduplication
Dataprofilering
Datavalidering
Datarevisjon
Enhetsforholdsmodellering
Dimensjonell modellering
Datatolkning
Datavisualisering
Beskrivende statistikk
Hypotesetesting
Regresjonsanalyse
Tidsserieanalyse
Korrelasjonsanalyse
Dataprøvetaking
Datautforskning
Dataaggregering
Datafiltrering
Datatransformasjon
Datavisualiseringsteknikker
Dataklassifisering
Dataklynging
Dataoppsummering
Geospatial analyse

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What roles can I use the Data Wrangling Test for?

Data analytiker
Dataforsker
Dataingeniør
Dataarkitekt
Forretningsanalytiker
Databaseadministrator
Datakvalitetsanalytiker
Datavisualiseringsspesialist
Machine Learning Engineer
Kvantitativ analytiker

How is the Data Wrangling 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

Identifisere mønstre og trender i data
Bruke datakranglingsteknikker for rengjøring av data
Optimalisering av datalagring og gjenfinning
Implementering av datatransformasjonsoperasjoner
Opprette datapipelinjer for automatisering
Utføre funksjonsteknikk for prediktiv modellering
Implementering av avansert datavisualisering
Gjennomføre hypotesetesting for datavalidering
Bruke maskinlæringsalgoritmer for prediktiv analyse
Designe datadrevne strategier for forretningsavgjørelser

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Ansettelseslederne mente at de gjennom de tekniske spørsmålene de stilte under panelintervjuene, var i stand til å fortelle hvilke kandidater som scoret bedre, og differensierte med de som ikke skåret like godt. De er svært fornøyd med kvaliteten på kandidatene som er på listen med Adaface-screeningen.

85%

Reduksjon i screeningstid

Se hele casestudien

Data Wrangling Hiring Test Vanlige spørsmål

Kan jeg kombinere flere ferdigheter til en tilpasset vurdering?

Ja absolutt. Tilpassede vurderinger er satt opp basert på stillingsbeskrivelsen din, og vil inneholde spørsmål om alle må-ha ferdigheter du spesifiserer.

Har du noen anti-juksende eller proktoreringsfunksjoner på plass?

Vi har følgende anti-juksede funksjoner på plass:

Ikke-googlable spørsmål
IP Proctoring
Nettproctoring
Webcam Proctoring
Deteksjon av plagiering
Sikker nettleser

Les mer om Proctoring -funksjonene.

Hvordan tolker jeg testresultater?

Den viktigste tingen å huske på er at en vurdering er et eliminasjonsverktøy, ikke et seleksjonsverktøy. En ferdighetsvurdering er optimalisert for å hjelpe deg med å eliminere kandidater som ikke er teknisk kvalifisert for rollen, det er ikke optimalisert for å hjelpe deg med å finne den beste kandidaten for rollen. Så den ideelle måten å bruke en vurdering på er å bestemme en terskelpoeng (vanligvis 55%, vi hjelper deg med å benchmark) og invitere alle kandidater som scorer over terskelen for de neste rundene med intervjuet.

Hvilken opplevelsesnivå kan jeg bruke denne testen til?

Hver ADAFACE -vurdering er tilpasset din stillingsbeskrivelse/ ideell kandidatperson (våre fageksperter vil velge de riktige spørsmålene for din vurdering fra vårt bibliotek med 10000+ spørsmål). Denne vurderingen kan tilpasses for ethvert opplevelsesnivå.

Får hver kandidat de samme spørsmålene?

Ja, det gjør det mye lettere for deg å sammenligne kandidater. Alternativer for MCQ -spørsmål og rekkefølgen på spørsmål er randomisert. Vi har anti-juksing/proctoring funksjoner på plass. I vår bedriftsplan har vi også muligheten til å lage flere versjoner av den samme vurderingen med spørsmål med lignende vanskelighetsnivåer.