Search test library by skills or roles
⌘ K

About the test:

TALEND在线测试使用基于方案的MCQ来评估候选人在TALEND ETL中的熟练程度,包括设计和开发ETL作业,实施数据集成过程并配置TALEND组件的能力。此外,该测试还评估了候选人对Talend Studio的知识,元数据管理,数据质量,与其他企业系统的集成以及常见的ETL和数据集成概念。该测试旨在评估候选人与Talend合作以有效设计和开发数据集成解决方案的能力。

Covered skills:

  • 塔伦德
  • etl
  • 数据治理
  • 云集成
  • 数据转换
  • 实时数据处理
  • 数据集成
  • 数据质量
  • 大数据
  • 主数据管理
  • 数据迁移

9 reasons why
9 reasons why

Adaface TALEND在线测试 is the most accurate way to shortlist TALEND数据工程师s



Reason #1

Tests for on-the-job skills

The TALEND在线测试 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:

  • 能够使用talend创建和管理数据集成作业
  • 精通ETL(提取,变换,负载)过程
  • 能够确保数据质量并实施数据治理
  • 擅长于合作大数据和云集成
  • 主数据管理方面的经验
  • 熟悉数据转换技术
  • 知识渊博的数据迁移
  • 处理实时数据处理的能力
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
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

这些只是我们库中有10,000多个问题的一个小样本。关于此的实际问题 TALEND在线测试 将是不可行的.

🧐 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:
 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
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:
 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
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:
 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
Solve
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
Solve
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
Solve
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
Solve
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
Solve
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
Solve

Medium

Dynamic Product API
Schema Evolution
Dynamic Data Types
API Integration

2 mins

Talend
Solve

Medium

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

3 mins

Talend
Solve

Medium

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

2 mins

Talend
Solve

Medium

Multi Select
JOIN
GROUP BY

2 mins

SQL
Solve

Medium

nth highest sales
Nested queries
User Defined Functions

3 mins

SQL
Solve

Medium

Select & IN
Nested queries

3 mins

SQL
Solve

Medium

Sorting Ubers
Nested queries
Join
Comparison operators

3 mins

SQL
Solve

Hard

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

2 mins

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

1200+ customers in 75 countries

customers in 75 countries
Brandon

借助 Adaface,我们能够将初步筛选流程优化达 75% 以上,为招聘经理和我们的人才招聘团队节省了宝贵的时间!


Brandon Lee, 人事主管, Love, Bonito

Reason #5

Designed for elimination, not selection

The most important thing while implementing the pre-employment TALEND在线测试 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在线测试 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

Reason #7

Detailed scorecards & benchmarks

Along with scorecards that report the performance of the candidate in detail, you also receive a comparative analysis against the company average and industry standards.

View sample scorecard
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在线测试

Why you should use TALEND在线测试?

The TALEND在线测试 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:

  • 使用TALEND整合来自各种来源的数据
  • 为数据检索和操作编写复杂的SQL查询
  • 使用TALEND执行ETL(提取,转换,负载)操作
  • 实施数据质量检查并确保数据准确性
  • 理解和应用数据治理原则
  • 使用大数据技术并处理大数据集
  • 使用TALEND集成基于云的系统和服务
  • 实施主数据管理解决方案
  • 使用talend进行数据转换和丰富
  • 将数据从传统系统迁移到新平台

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在线测试?

  • 数据集成

    数据集成是将来自不同来源和不同来源以及不同来源和协调数据组合和协调数据的过程系统成统一且一致的格式。它涉及提取数据,转换和清洁数据并将其加载到目标系统中,使组织能够对其数据进行整体视图。

  • etl </h4>

    etl(提取,变换,变换,变换,变换,变换,负载)是数据集成中用于从各种来源提取数据,将其转换为合适格式的过程,然后将其加载到目标系统中。它在确保数据质量和完整性以及使组织能够有效利用其数据方面起着至关重要的作用。

  • 数据质量

    数据质量是指准确性,完整性,一致性,一致性,一致性,一致性,一致性,一致性,一致性,一致性和数据的有效性。确保数据质量对于做出明智的决策和保持业务流程的可靠性至关重要。该技能衡量了识别和解决与数据质量有关的问题的能力。

  • 数据治理

    数据治理涉及组织内数据资产的整体管理和控制。它包括定义数据处理的政策,标准和准则,确保遵守法规以及建立数据质量,隐私和安全性的流程。该技能的衡量是为了评估候选人对数据治理原则和实践的理解。

  • 大数据

    大数据是指无法使用传统数据库工具和无法轻松管理的大数据集技术。它涵盖了大量结构化和非结构化数据的存储,处理和分析。该技能旨在评估候选人对大数据技术的知识及其使用大规模数据的能力。

  • 云集成

    云集成涉及将本地系统与云连接起来基于基于的应用程序和服务。它使组织能够利用云计算的可扩展性,灵活性和成本效益。该技能的衡量是为了评估候选人在云环境中集成和管理数据的能力。

  • 主数据管理

    主数据管理(MDM)是一项纪律,专注于管理和管理维护组织内的权威和一致的参考数据。它涉及为核心数据元素(例如客户,产品和供应商信息)创建一个可靠的真实来源。该技能的衡量是为了评估候选人对MDM概念的理解及其实施MDM解决方案的能力。

  • 数据转换

    数据转换是指从一种格式或结构转换数据的过程向另一个人,使其适用于不同的应用程序或系统。它涉及操纵,映射和丰富数据以满足特定的业务需求。该技能的衡量是为了评估候选人在设计和执行数据转换任务方面的熟练程度。

  • 数据迁移

    数据迁移是将数据从一个系统或存储格式传输到另一种系统的过程。它可能涉及从多个来源,升级系统或迁移到新平台的合并数据。该技能的衡量是为了评估候选人对数据迁移方法的了解及其确保数据成功传输的能力。

  • 实时数据处理

    实时数据处理是指在不延迟的情况下处理和分析数据到达时的能力。它使组织能够根据最新信息做出决策并采取行动。该技能的衡量是为了评估候选人对实时数据处理技术的理解及其构建高性能数据处理管道的能力。

  • 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在线测试 to be based on.

    Talend Studio
    数据集成
    ETL过程
    数据质量
    数据治理
    大数据集成
    云集成
    主数据管理
    数据转换
    数据迁移
    实时数据处理
    数据仓库
    数据分析
    数据清理
    数据建模
    元数据管理
    数据提取
    数据加载
    更改数据捕获
    错误处理
    模式设计
    SQL集成
    查询优化
    数据库连接
    尺寸建模
    数据复制
    数据同步
    数据映射
    数据验证
    数据掩盖
    数据血统
    性能调整
    并行处理
    工作流管理
    调度
    工作监控
    数据治理框架
    数据隐私
    数据安全
    数据归档
    数据虚拟化
    企业信息集成
    实时数据集成
    数据流
    数据科学整合
    云存储集成
    数据质量监视
    数据编目
    数据分析工具
    总数据管理实践
    数据迁移策略
    ETL最佳实践
    ETL工具比较
    ETL性能优化
    数据争吵
    实时分析

What roles can I use the TALEND在线测试 for?

  • TALEND数据工程师
  • TALEND ETL开发人员
  • 数据集成专家
  • 商业智能开发人员
  • 数据仓库开发人员
  • 大数据工程师
  • 云集成开发人员
  • 数据转换专家
  • TALEND解决方案建筑师

How is the TALEND在线测试 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

  • 处理实时数据流和事件
  • 在talend中设计和实施数据管道
  • 优化TAL的作业以进行性能和可伸缩性
  • 实施数据质量分析和监视
  • 管理和维护数据存储库
  • 使用TALEND构建数据集成工作流程
  • 确保集成过程中的数据安全和隐私
  • 设计和实施数据映射和转换
  • 执行数据验证和验证
  • 与利益相关者合作以收集要求并定义集成解决方案
Singapore government logo

招聘经理认为,通过小组面试中提出的技术问题,他们能够判断哪些候选人得分更高,并与得分较差的候选人区分开来。他们是 非常满意 通过 Adaface 筛选入围的候选人的质量。


85%
减少筛查时间

TALEND在线测试 常见问题解答

我可以将多个技能结合在一起,为一个自定义评估吗?

是的,一点没错。自定义评估是根据您的职位描述进行的,并将包括有关您指定的所有必备技能的问题。

您是否有任何反交换或策略功能?

我们具有以下反交易功能:

  • 不可解决的问题
  • IP策略
  • Web Protoring
  • 网络摄像头Proctoring
  • 窃检测
  • 安全浏览器

阅读有关[Proctoring功能](https://www.adaface.com/proctoring)的更多信息。

如何解释考试成绩?

要记住的主要问题是评估是消除工具,而不是选择工具。优化了技能评估,以帮助您消除在技术上没有资格担任该角色的候选人,它没有进行优化以帮助您找到该角色的最佳候选人。因此,使用评估的理想方法是确定阈值分数(通常为55%,我们为您提供基准测试),并邀请所有在下一轮面试中得分高于门槛的候选人。

我可以使用该测试的经验水平?

每个ADAFACE评估都是为您的职位描述/理想候选角色定制的(我们的主题专家将从我们的10000多个问题的图书馆中选择正确的问题)。可以为任何经验级别定制此评估。

每个候选人都会得到同样的问题吗?

是的,这使您比较候选人变得容易得多。 MCQ问题的选项和问题顺序是随机的。我们有[抗欺骗/策略](https://www.adaface.com/proctoring)功能。在我们的企业计划中,我们还可以选择使用类似难度级别的问题创建多个版本的相同评估。

我是候选人。我可以尝试练习测试吗?

不,不幸的是,我们目前不支持实践测试。但是,您可以使用我们的[示例问题](https://www.adaface.com/questions)进行练习。

使用此测试的成本是多少?

您可以查看我们的[定价计划](https://www.adaface.com/pricing/)。

我可以免费试用吗?

我刚刚搬到了一个付费计划。我如何要求自定义评估?

customers across world
Join 1200+ companies in 75+ countries.
立即尝试最候选的友好技能评估工具。
g2 badges
Ready to use the Adaface TALEND在线测试?
Ready to use the Adaface TALEND在线测试?
logo
40 min tests.
No trick questions.
Accurate shortlisting.
术语 隐私 信任指南

🌎选择您的语言

English Norsk Dansk Deutsche Nederlands Svenska Français Español Chinese (简体中文) Italiano Japanese (日本語) Polskie Português Russian (русский)
ada
Ada
● Online
Previous
Score: NA
Next
✖️