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About the test:

Talend Online-testen bruger scenariebaserede MCQ'er til at evaluere kandidater om deres færdigheder i Talend ETL, herunder evnen til at designe og udvikle ETL-job, implementere dataintegrationsprocesser og konfigurere Talend-komponenter. Derudover vurderer testen en kandidats viden om Talend Studio, Metadata Management, datakvalitet, integration med andre virksomhedssystemer og fælles ETL- og dataintegrationskoncepter. Testen sigter mod at evaluere en kandidats evne til at arbejde med Talend til at designe og udvikle dataintegrationsløsninger effektivt.

Covered skills:

  • Talend
  • ETL
  • Data -styring
  • Cloud -integration
  • Datatransformation
  • Databehandling af realtid
  • Dataintegration
  • Datakvalitet
  • Big data
  • Master Data Management
  • Datamigration

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9 reasons why
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:

  • I stand til at oprette og administrere dataintegrationsjob ved hjælp af Talend
  • Dygtige til ETL (uddrag, transformation, belastning) processer
  • I stand til at sikre datakvalitet og implementering af datastyring
  • Dygtige til at arbejde med big data og cloud -integration
  • Erfaret i masterdatastyring
  • Kendskab til datatransformationsteknikker
  • Vidende i datamigration
  • Evne til at håndtere realtid databehandling
Reason #2

No trick questions

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 kun en lille prøve fra vores bibliotek med 10.000+ spørgsmål. De faktiske spørgsmål om dette Talend online test vil være ikke-gåbart.

🧐 Question

Medium

Conditional Processing
Row Filtering
Component Linking
Job Design
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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:
 image
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
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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:
 image
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:
 image
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
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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
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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:
 image
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
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Consider the following SQL table:
 image
How many rows does the following SQL query return?
 image

Medium

nth highest sales
Nested queries
User Defined Functions
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Consider the following SQL table:
 image
Which of the following SQL commands will find the ‘nth highest Sales’ if it exists (returns null otherwise)?
 image

Medium

Select & IN
Nested queries
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Consider the following SQL table:
 image
Which of the following SQL queries would return the year when neither a football or cricket winner was chosen?
 image

Medium

Sorting Ubers
Nested queries
Join
Comparison operators
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Consider the following SQL table:
 image
What will be the first two tuples resulting from the following SQL command?
 image

Hard

With, AVG & SUM
MAX() MIN()
Aggregate functions
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Consider the following SQL table:
 image
How many tuples does the following query return?
 image
🧐 Question🔧 Skill

Medium

Conditional Processing
Row Filtering
Component Linking
Job Design

2 mins

Talend
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Medium

Dynamic Product API
Schema Evolution
Dynamic Data Types
API Integration

2 mins

Talend
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Medium

Multi-source Data Aggregation
Data Transformation
Joins
Lookup
Aggregation
Data Filters

3 mins

Talend
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Medium

Null Dates in tJavaRow
Java Programming
Null Safety
Date Manipulation
Exception Handling

2 mins

Talend
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Medium

Multi Select
JOIN
GROUP BY

2 mins

SQL
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Medium

nth highest sales
Nested queries
User Defined Functions

3 mins

SQL
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Medium

Select & IN
Nested queries

3 mins

SQL
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Medium

Sorting Ubers
Nested queries
Join
Comparison operators

3 mins

SQL
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Hard

With, AVG & SUM
MAX() MIN()
Aggregate functions

2 mins

SQL
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🧐 Question🔧 Skill💪 Difficulty⌛ Time
Conditional Processing
Row Filtering
Component Linking
Job Design
Talend
Medium2 mins
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Dynamic Product API
Schema Evolution
Dynamic Data Types
API Integration
Talend
Medium2 mins
Try practice test
Multi-source Data Aggregation
Data Transformation
Joins
Lookup
Aggregation
Data Filters
Talend
Medium3 mins
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Null Dates in tJavaRow
Java Programming
Null Safety
Date Manipulation
Exception Handling
Talend
Medium2 mins
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Multi Select
JOIN
GROUP BY
SQL
Medium2 mins
Try practice test
nth highest sales
Nested queries
User Defined Functions
SQL
Medium3 mins
Try practice test
Select & IN
Nested queries
SQL
Medium3 mins
Try practice test
Sorting Ubers
Nested queries
Join
Comparison operators
SQL
Medium3 mins
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With, AVG & SUM
MAX() MIN()
Aggregate functions
SQL
Hard2 mins
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Reason #4

1200+ customers in 75 countries

customers in 75 countries
Brandon

Med Adaface var vi i stand til at optimere vores indledende screeningsproces med op mod 75 %, hvilket frigjorde kostbar tid for både ansættelsesledere og vores talentanskaffelsesteam!


Brandon Lee, Leder af mennesker, 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.

invite candidates
Reason #7

Detailed scorecards & benchmarks

Se prøvescorekort
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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.

test completion rate
Reason #9

Advanced Proctoring


Learn more

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:

  • Integrering af data fra forskellige kilder ved hjælp af Talend
  • Skrivning af komplekse SQL -forespørgsler til dataindhentning og manipulation
  • Udførelse af ETL (uddrag, transform, belastning) operationer ved hjælp af Talend
  • Implementering af datakvalitetskontrol og sikre datanøjagtighed
  • Forståelse og anvendelse af principper for datastyring
  • Arbejder med big datateknologier og behandling af store datasæt
  • Integrering af skybaserede systemer og tjenester ved hjælp af Talend
  • Implementering af masterdatastyringsløsninger
  • Udførelse af datatransformation og berigelse ved hjælp af Talend
  • Migrerende data fra ældre systemer til nye platforme

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?

  • Talend

    Talend er en populær open source-dataintegrationsplatform, der gør det muligt for organisationer at oprette forbindelse, transformere og styre deres data på tværs af forskellige systemer. Det giver et omfattende sæt værktøjer og funktionaliteter til design, udvikling og implementering af dataintegrationsarbejdsgange.

  • dataintegration

    Dataintegration er processen med at kombinere og harmonisere data fra forskellige kilder og Systemer til et samlet og konsistent format. Det involverer at udtrække data, omdanne og rense dem og indlæse dem til et målsystem, hvilket gør det muligt for organisationer at have et holistisk overblik over deres data.

  • ETL

    ETL (uddrag, transform, transform, Belastning) er en proces, der bruges i dataintegration til at udtrække data fra forskellige kilder, omdanne dem til et passende format og indlæse det til et målsystem. Det spiller en afgørende rolle i at sikre datakvalitet og integritet samt gøre det muligt for organisationer at udnytte deres data effektivt.

  • datakvalitet

    Datakvalitet refererer til nøjagtigheden, fuldstændigheden, konsistensen, konsistensen, konsistensen, konsistens og gyldighed af data. At sikre datakvalitet er vigtig for at tage informerede beslutninger og opretholde pålideligheden af ​​forretningsprocesser. Denne færdighed måler evnen til at identificere og løse problemer relateret til datakvalitet.

  • Data Governance

    Data Governance involverer den overordnede styring og kontrol af dataaktiver i en organisation. Det omfatter definition af politikker, standarder og retningslinjer for datahåndtering, sikrer overholdelse af regler og etablering af processer for datakvalitet, privatliv og sikkerhed. Denne færdighed måles for at vurdere en kandidats forståelse af principper og praksis for datastyring.

  • big data

    Big Data refererer til store og komplekse datasæt, der ikke let kan styres ved hjælp af traditionelle databaseværktøjer og teknikker. Det omfatter lagring, behandling og analyse af store mængder strukturerede og ustrukturerede data. Denne færdighed måles for at evaluere en kandidats viden om big datateknologier og deres evne til at arbejde med store data.

  • Cloud-integration

    Cloud-integration involverer at forbinde on-premises systemer med sky -baserede applikationer og tjenester. Det gør det muligt for organisationer at udnytte skalerbarhed, fleksibilitet og omkostningseffektivitet af cloud computing. Denne færdighed måles for at vurdere en kandidats færdigheder i at integrere og styre data i et skymiljø.

  • masterdatastyring

    Master Data Management (MDM) er en disciplin, der fokuserer på styring og Vedligeholdelse af de autoritative og konsistente referencedata i en organisation. Det involverer at skabe en enkelt, pålidelig kilde til sandhed for kernedataelementer, såsom kunde-, produkt- og leverandørinformation. Denne færdighed måles for at evaluere en kandidats forståelse af MDM -koncepter og deres evne til at implementere MDM -løsninger.

  • datatransformation

    Datatransformation henviser til processen med at konvertere data fra et format eller struktur til en anden, hvilket gør det velegnet til forskellige applikationer eller systemer. Det involverer at manipulere, kortlægge og berige data for at imødekomme specifikke forretningskrav. Denne færdighed måles for at vurdere en kandidats færdigheder i at designe og udføre datatransformationsopgaver.

  • Data Migration

    Datamigration er processen med at overføre data fra et system eller lagringsformat til et andet. Det kan involvere konsolidering af data fra flere kilder, opgraderingssystemer eller migrere til en ny platform. Denne færdighed måles for at evaluere en kandidats viden om datamigrationsmetoder og deres evne til at sikre en vellykket overførsel af data.

  • realtid databehandling

    realtid databehandling henviser til Evnen til at håndtere og analysere data, når de ankommer, uden forsinkelse. Det gør det muligt for organisationer at tage beslutninger og tage handlinger baseret på ajourførte oplysninger. Denne færdighed måles for at vurdere en kandidats forståelse af realtidsdatabehandlingsteknologier og deres evne til at opbygge højtydende databehandlingsrørledninger.

  • 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
    Dataintegration
    ETL -processer
    Datakvalitet
    Data -styring
    Big Data Integration
    Cloud -integration
    Master Data Management
    Datatransformation
    Datamigration
    Databehandling af realtid
    Datalagring
    Dataprofilering
    Datarensning
    Datamodellering
    Metadata -styring
    Dataekstraktion
    Dataindlæsning
    Skift datafangst
    Fejlhåndtering
    Skema design
    SQL -integration
    Forespørgseloptimering
    Databaseforbindelse
    Dimensionel modellering
    Datareplikation
    Datasynkronisering
    Datakortlægning
    Data validering
    Datamaskering
    Dataforhold
    Performance Tuning
    Parallel behandling
    Workflow Management
    Planlægning
    Jobovervågning
    Rammer for datastyring
    Databeskyttelse
    Datasikkerhed
    Data arkivering
    Datavirtualisering
    Enterprise Information Integration
    Dataintegration i realtid
    Streaming af data
    Integration af datavidenskab
    Cloud Storage Integration
    Overvågning af datakvalitet
    Datakatalogisering
    Dataprofileringsværktøjer
    Master Data Management Practices
    Datamigrationsstrategier
    ETL bedste praksis
    ETL -værktøjssammenligning
    ETL Performance Optimization
    Data Wrangling
    Realtidsanalyse
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What roles can I use the Talend online test for?

  • Talend Data Engineer
  • Talend ETL -udvikler
  • Specialist i dataintegration
  • Business Intelligence Developer
  • Data Warehouse Developer
  • Big Data Engineer
  • Cloud Integration Developer
  • Datatransformationsspecialistm
  • 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

  • Behandling af datastrømme i realtid
  • Design og implementering af datarørledninger i Talend
  • Optimering af Talend -job til ydeevne og skalerbarhed
  • Implementering af profilering og overvågning af datakvalitet
  • Håndtering og vedligeholdelse af datalagringer
  • Bygning af dataintegrationsarbejdsgange ved hjælp af Talend
  • At sikre datasikkerhed og privatliv i integrationsprocesser
  • Design og implementering af datakortlægning og transformationer
  • Udførelse af datavalidering og verifikation
  • Samarbejde med interessenter for at indsamle krav og definere integrationsløsninger
Singapore government logo

Ansættelseslederne mente, at de gennem de tekniske spørgsmål, som de stillede under panelinterviewene, var i stand til at fortælle, hvilke kandidater der havde bedre score og differentieret sig med dem, der ikke scorede så godt. De er meget tilfreds med kvaliteten af ​​de kandidater, der er nomineret med Adaface-screeningen.


85%
Reduktion i screeningstid

Talend Hiring Test Ofte stillede spørgsmål

Kan jeg kombinere flere færdigheder i en brugerdefineret vurdering?

Ja absolut. Brugerdefinerede vurderinger er oprettet baseret på din jobbeskrivelse og vil omfatte spørgsmål om alle must-have-færdigheder, du angiver.

Har du nogen anti-cheating eller proctoring-funktioner på plads?

Vi har følgende anti-cheating-funktioner på plads:

  • Ikke-gåbare spørgsmål
  • IP Proctoring
  • Webproctoring
  • Webcam Proctoring
  • Detektion af plagiering
  • Sikker browser

Læs mere om Proctoring Features.

Hvordan fortolker jeg testresultater?

Den primære ting at huske på er, at en vurdering er et elimineringsværktøj, ikke et udvælgelsesværktøj. En færdighedsvurdering er optimeret for at hjælpe dig med at eliminere kandidater, der ikke er teknisk kvalificerede til rollen, den er ikke optimeret til at hjælpe dig med at finde den bedste kandidat til rollen. Så den ideelle måde at bruge en vurdering på er at beslutte en tærskelværdi (typisk 55%, vi hjælper dig med benchmark) og inviterer alle kandidater, der scorer over tærsklen for de næste interviewrunder.

Hvilken oplevelsesniveau kan jeg bruge denne test til?

Hver Adaface -vurdering tilpasses til din jobbeskrivelse/ ideel kandidatperson (vores emneeksperter vælger de rigtige spørgsmål til din vurdering fra vores bibliotek på 10000+ spørgsmål). Denne vurdering kan tilpasses til ethvert erfaringsniveau.

Får hver kandidat de samme spørgsmål?

Ja, det gør det meget lettere for dig at sammenligne kandidater. Valgmuligheder for MCQ -spørgsmål og rækkefølgen af ​​spørgsmål randomiseres. Vi har anti-cheating/proctoring funktioner på plads. I vores virksomhedsplan har vi også muligheden for at oprette flere versioner af den samme vurdering med spørgsmål om lignende vanskelighedsniveauer.

Jeg er kandidat. Kan jeg prøve en øvelsestest?

Nej. Desværre understøtter vi ikke praksisforsøg i øjeblikket. Du kan dog bruge vores eksempler på spørgsmål til praksis.

Hvad er omkostningerne ved at bruge denne test?

Du kan tjekke vores prisplaner.

Kan jeg få en gratis prøve?

Ja, du kan tilmelde dig gratis og forhåndsvise denne test.

Jeg flyttede lige til en betalt plan. Hvordan kan jeg anmode om en brugerdefineret vurdering?

Her er en hurtig guide til hvordan man anmoder om en brugerdefineret vurdering på adaface.

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