Talend Online -Test

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

Talend Datenintegration ETL Datenqualität Datenamt Große Daten Cloud -Integration Stammdatenverwaltung Datenumwandlung Datenmigration Echtzeitdatenverarbeitung

About the test:

Der Talend-Online-Test verwendet szenariobasierte MCQs, um Kandidaten über ihre Fähigkeiten in Talend ETL zu bewerten, einschließlich der Fähigkeit, ETL-Jobs zu entwerfen und zu entwickeln, Datenintegrationsprozesse zu implementieren und Talend-Komponenten zu konfigurieren. Darüber hinaus bewertet der Test das Wissen eines Kandidaten in Talend Studio, Metadatenmanagement, Datenqualität, Integration in andere Unternehmenssysteme sowie gemeinsame ETL- und Datenintegrationskonzepte. Der Test zielt darauf ab, die Fähigkeit eines Kandidaten zu bewerten, mit Talend zusammenzuarbeiten, um Datenintegrationslösungen effektiv zu entwerfen und zu entwickeln.

Covered skills:

Talend
ETL
Datenamt
Cloud -Integration
Datenumwandlung
Echtzeitdatenverarbeitung

Datenintegration
Datenqualität
Große Daten
Stammdatenverwaltung
Datenmigration

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9 reasons why

Adaface Talend Online -Test is the most accurate way to shortlist Talend -Dateningenieurs

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 der Lage, Datenintegrationsjobs mit Talend zu erstellen und zu verwalten
In ETL -Prozessen (Extrakt, Transformation, Belastung) kompetent
In der Lage, die Datenqualität sicherzustellen und Datenregierungsführung implementieren
Qualifiziert in der Arbeit mit Big Data und Cloud -Integration
Erfahrung im Stammdatenmanagement
Vertraut mit Datentransformationstechniken
Sachkenntnis in der Datenmigration
Fähigkeit zur Verarbeitung von Echtzeit-Datenverarbeitung

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

Dies sind nur ein kleines Beispiel aus unserer Bibliothek mit mehr als 10.000 Fragen. Die tatsächlichen Fragen dazu Talend Online -Test wird nichtgänger sein.

🧐 Question
Medium Conditional Processing Row Filtering Component Linking Job Design	Try practice test
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	Try practice test
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	Try practice test
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	Try practice test
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	Try practice test
Consider the following SQL table: How many rows does the following SQL query return?
Medium nth highest sales Nested queries User Defined Functions	Try practice test
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	Try practice test
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	Try practice test
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	Try practice test
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	Try practice test
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	Try practice test
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	Try practice test
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	Try practice test
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	Try practice test
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	Try practice test
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	Try practice test
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	Try practice test
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	Try practice test
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	Try practice test
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	Try practice test
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	Try practice test
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	Try practice test
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	Try practice test
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	Try practice test
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	Try practice test
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	Try practice test
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	Try practice test
Consider the following SQL table: How many tuples does the following query return?

Reason #4

1200+ customers in 75 countries

Mit Adaface konnten wir unseren Erstauswahlprozess um mehr als 75 % optimieren und so wertvolle Zeit sowohl für Personalmanager als auch für unser Talentakquiseteam gewinnen!

Brandon Lee, Leiter der Menschen, 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

Ansicht der Probe Scorecard

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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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Ansicht der Probe Scorecard

About the Talend Online -Test

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:

Daten aus verschiedenen Quellen mit Talend integrieren
Schreiben komplexer SQL -Abfragen zum Abrufen von Daten und Manipulationen
Durchführung von ETL -Operationen (Extrakt, Transformation, Last) mit Talend
Implementierung von Datenqualitätsprüfungen und Gewährleistung der Datengenauigkeit
Verständnis und Anwendung von Daten Governance -Prinzipien
Arbeiten mit Big -Data -Technologien und Verarbeitung großer Datensätze
Integration von Cloud-basierten Systemen und Diensten mit Talend
Implementierung von Lösungen für Stammdatenmanagementlösungen
Durchführung von Datenumwandlung und Anreicherung mit Talend
Migrieren von Daten von Legacy -Systemen auf neue Plattformen

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 ist eine beliebte Open-Source-Datenintegrationsplattform, mit der Unternehmen ihre Daten über verschiedene Systeme hinweg verbinden, transformieren und verwaltet werden können. Es bietet einen umfassenden Satz von Tools und Funktionen zum Entwerfen, Entwickeln und Bereitstellen von Datenintegrations -Workflows. Systeme in ein einheitliches und konsistentes Format. Es umfasst das Extrahieren von Daten, die Transformation und Reinigung und das Laden in ein Zielsystem, wodurch Unternehmen eine ganzheitliche Sicht auf ihre Daten haben. Last) ist ein Prozess, der in der Datenintegration verwendet wird, um Daten aus verschiedenen Quellen zu extrahieren, sie in ein geeignetes Format zu verwandeln und in ein Zielsystem zu laden. Es spielt eine entscheidende Rolle bei der Gewährleistung der Datenqualität und -integrität und ermöglicht Unternehmen, ihre Daten effektiv zu nutzen. und Gültigkeit von Daten. Die Gewährleistung der Datenqualität ist für fundierte Entscheidungen und die Aufrechterhaltung der Zuverlässigkeit von Geschäftsprozessen unerlässlich. Diese Fähigkeit misst die Fähigkeit, Probleme im Zusammenhang mit der Datenqualität zu identifizieren und zu beheben. Es umfasst die Definition von Richtlinien, Standards und Richtlinien für die Datenbearbeitung, die Einhaltung der Vorschriften und die Festlegung von Prozessen für Datenqualität, Datenschutz und Sicherheit. Diese Fähigkeit wird gemessen, um das Verständnis eines Kandidaten für Datengovernance -Prinzipien und -Praktiken zu bewerten. Techniken. Es umfasst die Speicherung, Verarbeitung und Analyse großer Mengen strukturierter und unstrukturierter Daten. Diese Fähigkeit wird gemessen, um das Wissen eines Kandidaten über Big-Data-Technologien und deren Fähigkeit, mit großen Daten zu arbeiten -basierte Anwendungen und Dienste. Es ermöglicht Unternehmen, die Skalierbarkeit, Flexibilität und Kosteneffizienz von Cloud Computing zu nutzen. Diese Fähigkeit wird gemessen, um die Fähigkeiten eines Kandidaten bei der Integration und Verwaltung von Daten in eine Cloud -Umgebung zu bewerten. Aufrechterhaltung der maßgeblichen und konsistenten Referenzdaten innerhalb einer Organisation. Dazu gehört es, eine einzelne, zuverlässige Quelle der Wahrheit für Kerndatenelemente wie Kunden-, Produkt- und Lieferanteninformationen zu erstellen. Diese Fähigkeit wird gemessen, um das Verständnis eines Kandidaten für MDM -Konzepte und deren Fähigkeit zur Implementierung von MDM -Lösungen zu bewerten. zu einem anderen, um es für verschiedene Anwendungen oder Systeme geeignet zu machen. Es umfasst die Manipulation, Kartierung und Anreicherung von Daten, um bestimmte Geschäftsanforderungen zu erfüllen. Diese Fähigkeit wird gemessen, um die Kenntnisse eines Kandidaten bei der Gestaltung und Ausführung von Datenumwandlungsaufgaben zu bewerten. Es kann die Konsolidierung von Daten aus mehreren Quellen, Upgrade von Systemen oder Migration auf eine neue Plattform beinhalten. Diese Fähigkeit wird gemessen, um das Wissen eines Kandidaten über Datenmigrationsmethoden und deren Fähigkeit zu bewerten, die erfolgreiche Datenübertragung zu gewährleisten. Die Fähigkeit, ohne Verzögerung Daten zu behandeln und zu analysieren, wenn sie eintrifft. Es ermöglicht Unternehmen, Entscheidungen zu treffen und Maßnahmen zu ergreifen, die auf aktuellen Informationen basieren. Diese Fähigkeit wird gemessen, um das Verständnis eines Kandidaten für Echtzeit-Datenverarbeitungstechnologien und deren Fähigkeit, Hochleistungsdatenverarbeitungspipelines aufzubauen, zu bewerten.
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
Datenintegration
ETL -Prozesse
Datenqualität
Datenamt
Big Data Integration
Cloud -Integration
Stammdatenverwaltung
Datenumwandlung
Datenmigration
Echtzeitdatenverarbeitung
Data Warehousing
Datenprofilerstellung
Datenbereinigung
Datenmodellierung
Metadatenmanagement
Datenextraktion
Datenbelastung
Datenerfassung ändern
Fehlerbehandlung
Schema -Design
SQL -Integration
Abfrageoptimierung
Datenbankkonnektivität
Dimensionsmodellierung
Datenreplikation
Datensynchronisation
Datenzuordnung
Datenvalidierung
Datenmaskierung
Datenlinie
Leistungsstimmung
Parallelverarbeitung
Workflow-Management
Planung
Jobüberwachung
Data Governance Frameworks
Datenprivatsphäre
Datensicherheit
Datenarchivierung
Datenvirtualisierung
Integration von Unternehmensinformationen
Echtzeitdatenintegration
Datenstreaming
Data Science Integration
Cloud -Speicherintegration
Datenqualitätsüberwachung
Datenkatalogisierung
Datenprofilierungswerkzeuge
Stammdatenmanagementpraktiken
Datenmigrationsstrategien
ETL Best Practices
ETL Tools -Vergleich
ETL -Leistungsoptimierung
Daten umstreiten
Echtzeitanalytik

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What roles can I use the Talend Online -Test for?

Talend -Dateningenieur
Talend ETL -Entwickler
Datenintegrationsspezialist
Business Intelligence -Entwickler
Data Warehouse -Entwickler
Big Data Engineer
Cloud -Integrationsentwickler
Datentransformationsspezialistin
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

Verarbeitung von Echtzeitdatenströmen und -ereignissen
Entwerfen und Implementieren von Datenpipelines in Talend
Optimierung von Talend -Jobs für Leistung und Skalierbarkeit
Implementierung von Datenqualitätsprofilen und Überwachung
Verwaltung und Wartung von Datenrepositorys
Erstellen von Workflows mit Datenintegration mit Talend
Gewährleistung der Datensicherheit und Datenschutz in Integrationsprozessen
Entwerfen und Implementieren von Datenzuordnung und Transformationen
Durchführung der Datenvalidierung und -überprüfung
Zusammenarbeit mit den Stakeholdern, um Anforderungen zu sammeln und Integrationslösungen zu definieren

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Ansicht der Probe Scorecard

Die Personalmanager hatten das Gefühl, dass sie durch die technischen Fragen, die sie während der Panel-Interviews stellten, erkennen konnten, welche Kandidaten bessere Ergebnisse erzielten, und sie von denen unterscheiden konnten, die nicht so gut abschnitten. Sie sind Sehr zufrieden mit der Qualität der Kandidaten, die beim Adaface-Screening in die engere Auswahl kommen.

85%

Verringerung der Screening -Zeit

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Talend Online -Test FAQs

Kann ich mehrere Fähigkeiten zu einer benutzerdefinierten Bewertung kombinieren?

Ja absolut. Basierend auf Ihrer Stellenbeschreibung werden benutzerdefinierte Bewertungen eingerichtet und enthalten Fragen zu allen von Ihnen angegebenen Must-Have-Fähigkeiten.

Haben Sie Anti-Cheating- oder Proctoring-Funktionen?

Wir haben die folgenden Anti-Cheating-Funktionen:

Nicht-Googling-Fragen
IP -Verbreitung
Web -Verbreitung
Webcam -Proctoring
Plagiaterkennung
sicherer Browser

Lesen Sie mehr über die Proctoring -Funktionen.

Wie interpretiere ich die Testergebnisse?

Die wichtigste Sache, die Sie beachten sollten, ist, dass eine Bewertung ein Eliminierungswerkzeug ist, kein Auswahlwerkzeug. Eine Bewertung der Qualifikationsbewertung wird optimiert, um Ihnen zu helfen, Kandidaten zu beseitigen, die technisch nicht für die Rolle qualifiziert sind. Sie ist nicht optimiert, um Ihnen dabei zu helfen, den besten Kandidaten für die Rolle zu finden. Die ideale Möglichkeit, eine Bewertung zu verwenden, besteht also darin, einen Schwellenwert zu entscheiden (in der Regel 55%, wir helfen Ihnen bei der Benchmark) und alle Kandidaten einladen, die für die nächsten Interviewrunden über dem Schwellenwert punkten.

Für welche Erfahrung kann ich diesen Test verwenden?

Jede Adaface -Bewertung ist an Ihre Stellenbeschreibung/ ideale Kandidatenpersönlichkeit angepasst (unsere Experten für Fache werden die richtigen Fragen für Ihre Bewertung aus unserer Bibliothek mit über 10000 Fragen auswählen). Diese Einschätzung kann für jede Erfahrungsstufe angepasst werden.

Bekommt jeder Kandidat die gleichen Fragen?

Ja, es macht es Ihnen viel einfacher, Kandidaten zu vergleichen. Optionen für MCQ -Fragen und die Reihenfolge der Fragen werden randomisiert. Wir haben Anti-Cheating/Proctoring Funktionen. In unserem Unternehmensplan haben wir auch die Möglichkeit, mehrere Versionen derselben Bewertung mit Fragen mit ähnlichen Schwierigkeitsgraden zu erstellen.