Why you should use Talend Online Test?

The Talend Online 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: Gegevens integreren uit verschillende bronnen met behulp van Talend Complexe SQL -query's schrijven voor het ophalen en manipuleren van gegevens Het uitvoeren van ETL -bewerkingen (extract, transformeren, laden) met behulp van Talend Gegevenskwaliteitscontroles implementeren en gegevensnauwkeurigheid waarborgen Principes van gegevensbeheer begrijpen en toepassen Werken met big data -technologieën en het verwerken van grote datasets Integratie van cloudgebaseerde systemen en services met behulp van Talend Master Data Management Solutions implementeren Gegevenstransformatie en verrijking uitvoeren met Talend Gegevens migreren van legacy -systemen naar nieuwe platforms

Talend Online Test

Q: What topics are covered in the Talend Online Test?

Talend Gegevens integratie ETL Data kwaliteit Data Governance Big Data Wolkenintegratie Master Data Management Gegevenstransformatie Data migratie Realtime gegevensverwerking

About the test:

De Talend Online Test maakt gebruik van scenario-gebaseerde MCQ's om kandidaten te evalueren op hun vaardigheid in Talend ETL, inclusief de mogelijkheid om ETL-taken te ontwerpen en te ontwikkelen, gegevensintegratieprocessen te implementeren en talenendcomponenten te configureren. Bovendien beoordeelt de test de kennis van een kandidaat van Talend Studio, metagegevensbeheer, gegevenskwaliteit, integratie met andere bedrijfssystemen en gemeenschappelijke ETL- en data -integratieconcepten. De test is bedoeld om het vermogen van een kandidaat te evalueren om samen te werken met Talend om oplossingen voor gegevensintegratie effectief te ontwerpen en te ontwikkelen.

Covered skills:

Talend
ETL
Data Governance
Wolkenintegratie
Gegevenstransformatie
Realtime gegevensverwerking

Gegevens integratie
Data kwaliteit
Big Data
Master Data Management
Data migratie

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9 reasons why

Adaface Talend Test is the most accurate way to shortlist Talend Data Engineers

Reason #1

Tests for on-the-job skills

The Talend 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 taken voor gegevensintegratie te maken en te beheren met Talend
Bekwaam in ETL (extract, transformeren, belasting) processen
In staat om datakwaliteit te waarborgen en gegevensbeheer te implementeren
Bekwaam in het werken met big data en cloud -integratie
Ervaring met master Data Management
Bekend met gegevenstransformatietechnieken
Goed geïnformeerd in gegevensmigratie
Mogelijkheid om realtime gegevensverwerking af te handelen

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 Talend Online Test zal niet-googelbaar zijn.

🧐 Question
Medium Conditional Processing Row Filtering Component Linking Job Design	Solve
Consider a Talend job that reads rows from a tFileInputDelimited component and intends to process them through a series of transformations. Here's a pseudocode representation of a segment of your Talend job: You need to implement this logic within your Talend job such that rows with a "columnValue" greater than 100 follow one transformation path and others follow a different transformation path. Which of the following actions would help achieve this desired behavior? A: Use a tFlowToIterate component after the tFileInputDelimited to iterate over rows and use a Java condition to route the data. B: In the tMap component, set filters on the output links to achieve conditional routing based on "columnValue". C: Place two tMap components side by side after tFileInputDelimited and use "columnValue" in each to filter rows. D: Use a tSplitRow component after tFileInputDelimited to split rows based on the condition and connect to respective tMap components. E: Implement a custom code component like tJavaRow to determine the flow of rows.
Medium Dynamic Product API Schema Evolution Dynamic Data Types API Integration	Solve
You're building a Talend job that integrates with an e-commerce platform's Product API. Over time, the platform has added, removed, or changed fields within the API response, making it a challenge to keep up with the schema changes. A typical API response might look like: However, fields like specs might have additional attributes in the future, or some fields might be deprecated. The primary goal of your Talend job is: Given this scenario, how should you best handle the dynamic nature of the Product API schema in your Talend job? A: Use tExtractJSONFields and adjust the XPath query every time the API changes. B: Set a fixed schema in tMap based on the most common fields and ignore new additions. C: Define the input schema of tMap as "Dynamic", and map necessary fields to a stable output schema. D: Set the tOutputDB schema to "Dynamic" and let the database adjust to incoming changes. E: Process the raw JSON strings directly in tMap and use string manipulations for transformations.
Medium Multi-source Data Aggregation Data Transformation Joins Lookup Aggregation Data Filters	Solve
You're working with three different data sources in a Talend job: a MySQL table (users), an Oracle table (transactions), and a CSV file (rewards). The goal is to create a report containing the user's name, total transaction amount, and reward points, but only for users who have both made a transaction and earned rewards. Here are the key columns from each source: - users: user_id, user_name - transactions: trans_id, user_id, amount - rewards: reward_id, user_id, points Which of the following sequences best accomplishes this? A: Use tMySQLInput, tOracleInput, and tFileInputDelimited in parallel -> tDenormalize to combine all results. Filter and aggregate results using tMap and then pass to tOutput. B: Use tMySQLInput and tOracleInput in parallel -> tJoin to combine results on user_id. Use tFilterRow to filter transactions and then join the filtered result with tFileInputDelimited using tMap. C: Use tMySQLInput -> tMap to join with tOracleInput based on user_id. Use another tMap to join the result with tFileInputDelimited. Aggregate results using tAggregateRow based on user_name, and filter using tFilterRow. D: Use tMySQLInput -> tMap to join with tOracleInput based on user_id. Then, join the result with tFileInputDelimited on user_id. Apply filters in tMap to exclude rows where users neither made a transaction nor earned rewards. E: Use tMySQLInput -> tMap to lookup and join with tFileInputDelimited based on user_id. Then, join this result with tOracleInput using another tMap. Apply filters in the final tMap to only include the desired rows.
Medium Null Dates in tJavaRow Java Programming Null Safety Date Manipulation Exception Handling	Solve
You're designing a Talend job to process e-commerce transactions. Each record has an "interactionType" field and a lastPurchase date field. For records with "SALE" as the interaction type, you want to calculate the number of days since the lastPurchase. However, the lastPurchase field can be null due to certain circumstances. Here's the Java code within the tJavaRow component: Which of the following statements is TRUE regarding the code? A: If the lastPurchase field is null, the code will throw a runtime exception. B: The daysSinceLastPurchase field is set to -1 solely in case of a date parsing error. C: All records with "SALE" as the interaction type will invariably have a non-negative daysSinceLastPurchase value. D: The code inherently assumes that every transaction of type "SALE" contains a valid lastPurchase date.
Medium Multi Select JOIN GROUP BY	Solve
Consider the following SQL table: How many rows does the following SQL query return?
Medium nth highest sales Nested queries User Defined Functions	Solve
Consider the following SQL table: Which of the following SQL commands will find the ‘nth highest Sales’ if it exists (returns null otherwise)?
Medium Select & IN Nested queries	Solve
Consider the following SQL table: Which of the following SQL queries would return the year when neither a football or cricket winner was chosen?
Medium Sorting Ubers Nested queries Join Comparison operators	Solve
Consider the following SQL table: What will be the first two tuples resulting from the following SQL command?
Hard With, AVG & SUM MAX() MIN() Aggregate functions	Solve
Consider the following SQL table: How many tuples does the following query return?

	🧐 Question	🔧 Skill
	Medium Conditional Processing Row Filtering Component Linking Job Design	2 mins Talend	Solve
Consider a Talend job that reads rows from a tFileInputDelimited component and intends to process them through a series of transformations. Here's a pseudocode representation of a segment of your Talend job: You need to implement this logic within your Talend job such that rows with a "columnValue" greater than 100 follow one transformation path and others follow a different transformation path. Which of the following actions would help achieve this desired behavior? A: Use a tFlowToIterate component after the tFileInputDelimited to iterate over rows and use a Java condition to route the data. B: In the tMap component, set filters on the output links to achieve conditional routing based on "columnValue". C: Place two tMap components side by side after tFileInputDelimited and use "columnValue" in each to filter rows. D: Use a tSplitRow component after tFileInputDelimited to split rows based on the condition and connect to respective tMap components. E: Implement a custom code component like tJavaRow to determine the flow of rows.
	Medium Dynamic Product API Schema Evolution Dynamic Data Types API Integration	2 mins Talend	Solve
You're building a Talend job that integrates with an e-commerce platform's Product API. Over time, the platform has added, removed, or changed fields within the API response, making it a challenge to keep up with the schema changes. A typical API response might look like: However, fields like specs might have additional attributes in the future, or some fields might be deprecated. The primary goal of your Talend job is: Given this scenario, how should you best handle the dynamic nature of the Product API schema in your Talend job? A: Use tExtractJSONFields and adjust the XPath query every time the API changes. B: Set a fixed schema in tMap based on the most common fields and ignore new additions. C: Define the input schema of tMap as "Dynamic", and map necessary fields to a stable output schema. D: Set the tOutputDB schema to "Dynamic" and let the database adjust to incoming changes. E: Process the raw JSON strings directly in tMap and use string manipulations for transformations.
	Medium Multi-source Data Aggregation Data Transformation Joins Lookup Aggregation Data Filters	3 mins Talend	Solve
You're working with three different data sources in a Talend job: a MySQL table (users), an Oracle table (transactions), and a CSV file (rewards). The goal is to create a report containing the user's name, total transaction amount, and reward points, but only for users who have both made a transaction and earned rewards. Here are the key columns from each source: - users: user_id, user_name - transactions: trans_id, user_id, amount - rewards: reward_id, user_id, points Which of the following sequences best accomplishes this? A: Use tMySQLInput, tOracleInput, and tFileInputDelimited in parallel -> tDenormalize to combine all results. Filter and aggregate results using tMap and then pass to tOutput. B: Use tMySQLInput and tOracleInput in parallel -> tJoin to combine results on user_id. Use tFilterRow to filter transactions and then join the filtered result with tFileInputDelimited using tMap. C: Use tMySQLInput -> tMap to join with tOracleInput based on user_id. Use another tMap to join the result with tFileInputDelimited. Aggregate results using tAggregateRow based on user_name, and filter using tFilterRow. D: Use tMySQLInput -> tMap to join with tOracleInput based on user_id. Then, join the result with tFileInputDelimited on user_id. Apply filters in tMap to exclude rows where users neither made a transaction nor earned rewards. E: Use tMySQLInput -> tMap to lookup and join with tFileInputDelimited based on user_id. Then, join this result with tOracleInput using another tMap. Apply filters in the final tMap to only include the desired rows.
	Medium Null Dates in tJavaRow Java Programming Null Safety Date Manipulation Exception Handling	2 mins Talend	Solve
You're designing a Talend job to process e-commerce transactions. Each record has an "interactionType" field and a lastPurchase date field. For records with "SALE" as the interaction type, you want to calculate the number of days since the lastPurchase. However, the lastPurchase field can be null due to certain circumstances. Here's the Java code within the tJavaRow component: Which of the following statements is TRUE regarding the code? A: If the lastPurchase field is null, the code will throw a runtime exception. B: The daysSinceLastPurchase field is set to -1 solely in case of a date parsing error. C: All records with "SALE" as the interaction type will invariably have a non-negative daysSinceLastPurchase value. D: The code inherently assumes that every transaction of type "SALE" contains a valid lastPurchase date.
	Medium Multi Select JOIN GROUP BY	2 mins SQL	Solve
Consider the following SQL table: How many rows does the following SQL query return?
	Medium nth highest sales Nested queries User Defined Functions	3 mins SQL	Solve
Consider the following SQL table: Which of the following SQL commands will find the ‘nth highest Sales’ if it exists (returns null otherwise)?
	Medium Select & IN Nested queries	3 mins SQL	Solve
Consider the following SQL table: Which of the following SQL queries would return the year when neither a football or cricket winner was chosen?
	Medium Sorting Ubers Nested queries Join Comparison operators	3 mins SQL	Solve
Consider the following SQL table: What will be the first two tuples resulting from the following SQL command?
	Hard With, AVG & SUM MAX() MIN() Aggregate functions	2 mins SQL	Solve
Consider the following SQL table: How many tuples does the following query return?

	🧐 Question	🔧 Skill	💪 Difficulty	⌛ Time
	Conditional Processing Row Filtering Component Linking Job Design	Talend	Medium	2 mins	Solve
Consider a Talend job that reads rows from a tFileInputDelimited component and intends to process them through a series of transformations. Here's a pseudocode representation of a segment of your Talend job: You need to implement this logic within your Talend job such that rows with a "columnValue" greater than 100 follow one transformation path and others follow a different transformation path. Which of the following actions would help achieve this desired behavior? A: Use a tFlowToIterate component after the tFileInputDelimited to iterate over rows and use a Java condition to route the data. B: In the tMap component, set filters on the output links to achieve conditional routing based on "columnValue". C: Place two tMap components side by side after tFileInputDelimited and use "columnValue" in each to filter rows. D: Use a tSplitRow component after tFileInputDelimited to split rows based on the condition and connect to respective tMap components. E: Implement a custom code component like tJavaRow to determine the flow of rows.
	Dynamic Product API Schema Evolution Dynamic Data Types API Integration	Talend	Medium	2 mins	Solve
You're building a Talend job that integrates with an e-commerce platform's Product API. Over time, the platform has added, removed, or changed fields within the API response, making it a challenge to keep up with the schema changes. A typical API response might look like: However, fields like specs might have additional attributes in the future, or some fields might be deprecated. The primary goal of your Talend job is: Given this scenario, how should you best handle the dynamic nature of the Product API schema in your Talend job? A: Use tExtractJSONFields and adjust the XPath query every time the API changes. B: Set a fixed schema in tMap based on the most common fields and ignore new additions. C: Define the input schema of tMap as "Dynamic", and map necessary fields to a stable output schema. D: Set the tOutputDB schema to "Dynamic" and let the database adjust to incoming changes. E: Process the raw JSON strings directly in tMap and use string manipulations for transformations.
	Multi-source Data Aggregation Data Transformation Joins Lookup Aggregation Data Filters	Talend	Medium	3 mins	Solve
You're working with three different data sources in a Talend job: a MySQL table (users), an Oracle table (transactions), and a CSV file (rewards). The goal is to create a report containing the user's name, total transaction amount, and reward points, but only for users who have both made a transaction and earned rewards. Here are the key columns from each source: - users: user_id, user_name - transactions: trans_id, user_id, amount - rewards: reward_id, user_id, points Which of the following sequences best accomplishes this? A: Use tMySQLInput, tOracleInput, and tFileInputDelimited in parallel -> tDenormalize to combine all results. Filter and aggregate results using tMap and then pass to tOutput. B: Use tMySQLInput and tOracleInput in parallel -> tJoin to combine results on user_id. Use tFilterRow to filter transactions and then join the filtered result with tFileInputDelimited using tMap. C: Use tMySQLInput -> tMap to join with tOracleInput based on user_id. Use another tMap to join the result with tFileInputDelimited. Aggregate results using tAggregateRow based on user_name, and filter using tFilterRow. D: Use tMySQLInput -> tMap to join with tOracleInput based on user_id. Then, join the result with tFileInputDelimited on user_id. Apply filters in tMap to exclude rows where users neither made a transaction nor earned rewards. E: Use tMySQLInput -> tMap to lookup and join with tFileInputDelimited based on user_id. Then, join this result with tOracleInput using another tMap. Apply filters in the final tMap to only include the desired rows.
	Null Dates in tJavaRow Java Programming Null Safety Date Manipulation Exception Handling	Talend	Medium	2 mins	Solve
You're designing a Talend job to process e-commerce transactions. Each record has an "interactionType" field and a lastPurchase date field. For records with "SALE" as the interaction type, you want to calculate the number of days since the lastPurchase. However, the lastPurchase field can be null due to certain circumstances. Here's the Java code within the tJavaRow component: Which of the following statements is TRUE regarding the code? A: If the lastPurchase field is null, the code will throw a runtime exception. B: The daysSinceLastPurchase field is set to -1 solely in case of a date parsing error. C: All records with "SALE" as the interaction type will invariably have a non-negative daysSinceLastPurchase value. D: The code inherently assumes that every transaction of type "SALE" contains a valid lastPurchase date.
	Multi Select JOIN GROUP BY	SQL	Medium	2 mins	Solve
Consider the following SQL table: How many rows does the following SQL query return?
	nth highest sales Nested queries User Defined Functions	SQL	Medium	3 mins	Solve
Consider the following SQL table: Which of the following SQL commands will find the ‘nth highest Sales’ if it exists (returns null otherwise)?
	Select & IN Nested queries	SQL	Medium	3 mins	Solve
Consider the following SQL table: Which of the following SQL queries would return the year when neither a football or cricket winner was chosen?
	Sorting Ubers Nested queries Join Comparison operators	SQL	Medium	3 mins	Solve
Consider the following SQL table: What will be the first two tuples resulting from the following SQL command?
	With, AVG & SUM MAX() MIN() Aggregate functions	SQL	Hard	2 mins	Solve
Consider the following SQL table: How many tuples does the following query return?

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 Talend Online 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 Talend Online 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 Talend Assessment Test

Why you should use Pre-employment Talend Online Test?

The Talend Online 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:

Gegevens integreren uit verschillende bronnen met behulp van Talend
Complexe SQL -query's schrijven voor het ophalen en manipuleren van gegevens
Het uitvoeren van ETL -bewerkingen (extract, transformeren, laden) met behulp van Talend
Gegevenskwaliteitscontroles implementeren en gegevensnauwkeurigheid waarborgen
Principes van gegevensbeheer begrijpen en toepassen
Werken met big data -technologieën en het verwerken van grote datasets
Integratie van cloudgebaseerde systemen en services met behulp van Talend
Master Data Management Solutions implementeren
Gegevenstransformatie en verrijking uitvoeren met Talend
Gegevens migreren van legacy -systemen naar nieuwe platforms

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 Talend Online Test?

Data Integration
Gegevensintegratie is het proces van het combineren en harmoniseren van gegevens uit verschillende bronnen en systemen in een uniform en consistent formaat. Het omvat het extraheren van gegevens, transformeren en reinigen en het laden in een doelsysteem, waardoor organisaties een holistisch beeld van hun gegevens kunnen hebben.
etl
ETL (extract, transformeren, Load) is een proces dat wordt gebruikt in gegevensintegratie om gegevens uit verschillende bronnen te extraheren, om te zetten in een geschikt formaat en deze te laden in een doelsysteem. Het speelt een cruciale rol bij het waarborgen van de gegevenskwaliteit en integriteit, evenals organisaties in staat te stellen hun gegevens effectief te benutten.
Datakwaliteit
Datakwaliteit verwijst naar de nauwkeurigheid, volledigheid, consistentie, en geldigheid van gegevens. Ervoor zorgen dat de gegevenskwaliteit essentieel is voor het nemen van geïnformeerde beslissingen en het handhaven van de betrouwbaarheid van bedrijfsprocessen. Deze vaardigheid meet het vermogen om problemen met betrekking tot de gegevenskwaliteit te identificeren en op te lossen.
Data Governance
Gegevensbeheer omvat het algemene beheer en de controle van gegevensactiva binnen een organisatie. Het omvat het definiëren van beleid, normen en richtlijnen voor gegevensverwerking, het waarborgen van de naleving van de voorschriften en het opzetten van processen voor gegevenskwaliteit, privacy en beveiliging. Deze vaardigheid wordt gemeten om het begrip van een kandidaat van gegevensbeheerprincipes en -praktijken te beoordelen.
big data
Big data verwijst naar grote en complexe datasets die niet eenvoudig kunnen worden beheerd met behulp van traditionele databasetools en technieken. Het omvat de opslag, verwerking en analyse van enorme hoeveelheden gestructureerde en ongestructureerde gegevens. Deze vaardigheid wordt gemeten om de kennis van een kandidaat van big data-technologieën en hun vermogen om te werken met grootschalige gegevens evalueren.
cloud-integratie
Cloud-integratie omvat het verbinden van on-premises systemen met cloud met cloud -Gebaseerde applicaties en services. Het stelt organisaties in staat om de schaalbaarheid, flexibiliteit en kosteneffectiviteit van cloud computing te benutten. Deze vaardigheid wordt gemeten om de vaardigheid van een kandidaat te beoordelen bij het integreren en beheren van gegevens in een cloudomgeving.
Master Data Management
Master Data Management (MDM) is een discipline die zich richt op het beheren en het onderhouden van de gezaghebbende en consistente referentiegegevens binnen een organisatie. Het omvat het creëren van een enkele, betrouwbare bron van waarheid voor kerngegevenselementen, zoals klant-, product- en leveranciersinformatie. Deze vaardigheid wordt gemeten om het begrip van een kandidaat van MDM -concepten en hun vermogen om MDM -oplossingen te implementeren te evalueren.
Data Transformation
Data -transformatie verwijst naar het proces van het converteren van gegevens uit één indeling of structuur aan een ander, waardoor het geschikt is voor verschillende toepassingen of systemen. Het omvat het manipuleren, in kaart brengen en verrijken van gegevens om aan specifieke zakelijke vereisten te voldoen. Deze vaardigheid wordt gemeten om de vaardigheid van een kandidaat bij het ontwerpen en uitvoeren van gegevenstransformatietaken te beoordelen.
Data Migration
Gegevensmigratie is het proces van het overbrengen van gegevens van het ene systeem of opslagindeling naar het andere. Het kan het consolideren van gegevens uit meerdere bronnen, upgradensystemen of migreren naar een nieuw platform omvatten. Deze vaardigheid wordt gemeten om de kennis van een kandidaat van gegevensmigratiemethoden te evalueren en hun vermogen om de succesvolle overdracht van gegevens te garanderen.
realtime gegevensverwerking
Real-time gegevensverwerking verwijst naar De mogelijkheid om gegevens te verwerken en te analyseren wanneer deze arriveert, zonder enige vertraging. Het stelt organisaties in staat om beslissingen te nemen en acties te ondernemen op basis van actuele informatie. Deze vaardigheid wordt gemeten om het begrip van een kandidaat van realtime gegevensverwerkingstechnologieën te beoordelen en hun vermogen om pijpleidingen voor het bouwen van high-performance gegevensverwerking te bouwen.
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 Talend Online Test to be based on.
Talend Studio
Gegevens integratie
ETL -processen
Data kwaliteit
Data Governance
Big data -integratie
Wolkenintegratie
Master Data Management
Gegevenstransformatie
Data migratie
Realtime gegevensverwerking
Data opslagplaats
Gegevensprofilering
Data-opschoning
Datamodellering
Metagegevensbeheer
Data-extractie
Gegevens laden
Wijzig gegevensopvang
Foutafhandeling
Schemaontwerp
SQL -integratie
Query -optimalisatie
Database -connectiviteit
Dimensionale modellering
Gegevensreplicatie
Gegevenssynchronisatie
Gegevensmapping
Gegevensvalidatie
Gegevensmaskering
Data -afkomst
Afstemming van prestaties
Parallelle verwerking
Workflow management
Het roosteren
Taakmonitoring
Gegevensbeheerkaders
Data Privacy
Dataveiligheid
Data -archivering
Gegevensvirtualisatie
Enterprise Information Integration
Real-time gegevensintegratie
Gegevensstreaming
Integratie van data science
Wolkenopslagintegratie
Monitoring van de gegevenskwaliteit
Data -catalogi
Gegevensprofileringstools
Master Data Management Practices
Gegevensmigratiestrategieën
ETL best practices
ETL Tools Vergelijking
ETL -prestatie -optimalisatie
Gegevens ruzie
Real-time analyse

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What roles can I use the Talend Online Test for?

Talend Data Engineer
Talend ETL -ontwikkelaar
Gegevensintegratiespecialist
Business Intelligence Developer
Developer
Big Data Engineer
Developer van de cloudintegratie
Gegevenstransformatiespecialistm
Talend Solution Architect

How is the Talend 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

Het verwerken van realtime gegevensstromen en gebeurtenissen
Datapijplijnen ontwerpen en implementeren in Talend
Talend Jobs optimaliseren voor prestaties en schaalbaarheid
Profilering en monitoring van de gegevenskwaliteit implementeren
Het beheren en onderhouden van gegevensrepositories
Workflows voor gegevensintegratie bouwen met Talend
Zorgen voor gegevensbeveiliging en privacy in integratieprocessen
Het ontwerpen en implementeren van gegevensmapping en transformaties
Gegevensvalidatie en verificatie uitvoeren
Werk samen met belanghebbenden om vereisten te verzamelen en integratieoplossingen te definiëren

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Bekijk Sample Scorecard

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

Bekijk volledige case study

Talend 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.