Data and analytics assessment tests for hiring
Compare 22 intermediate data and analytics assessment tests for roles in analysis, statistics, data preparation, visualization, and the platforms analysts use.
Het korte antwoord
These 22 intermediate, multiple-choice tests assess skills in statistics, data preparation, analysis, visualization, and data platforms. They suit employers hiring analysts, data scientists, engineers, BI and reporting developers, and other roles that work with data. Use tests tied to the role’s tasks, and treat results as evidence for a person to review.
22 tests
Apache Spark for Data Engineers
10 minuten · 15 vragen · Intermediate
Multiple choice
See the testProgrammeervaardighedenData Analysis Using R
10 minuten · 15 vragen · Intermediate
Multiple choice
See the testSoftwarevaardighedenData Analytics in Amazon Web Services (AWS)
10 minuten · 15 vragen · Intermediate
Multiple choice
See the testProgrammeervaardighedenData Analytics in Azure
10 minuten · 15 vragen · Intermediate
Multiple choice
See the testSoftwarevaardighedenData Analytics in Excel
10 minuten · 15 vragen · Intermediate
Multiple choice
See the testSoftwarevaardighedenData Analytics in Google Cloud Platform (GCP)
10 minuten · 15 vragen · Intermediate
Multiple choice
See the testFunctiegebonden vaardighedenData Extraction, Transformation, and Loading (ETL)
10 minuten · 15 vragen · Intermediate
Multiple choice
See the testFunctiegebonden vaardighedenData Modeling Concepts
10 minuten · 15 vragen · Intermediate
Multiple choice
See the testFunctiegebonden vaardighedenData Science
10 minuten · 20 vragen · Intermediate
Multiple choice
See the testFunctiegebonden vaardighedenData Storytelling
10 minuten · 15 vragen · Intermediate
Multiple choice
See the testFunctiegebonden vaardighedenData Wrangling
10 minuten · 15 vragen · Intermediate
Multiple choice
See the testFunctiegebonden vaardighedenData-Driven Decision Making
10 minuten · 15 vragen · Intermediate
Multiple choice
See the testFunctiegebonden vaardighedenExploratory Data Analysis
10 minuten · 15 vragen · Intermediate
Multiple choice
See the testFunctiegebonden vaardighedenFundamentals of Statistics and Probability
10 minuten · 15 vragen · Intermediate
Multiple choice
See the testProgrammeervaardighedenMatplotlib
10 minuten · 15 vragen · Intermediate
Multiple choice
See the testProgrammeervaardighedenNumPy
10 minuten · 16 vragen · Intermediate
Multiple choice
See the testProgrammeervaardighedenPandas
12 minuten · 18 vragen · Intermediate
Multiple choice
See the testSoftwarevaardighedenPower BI
10 minuten · 15 vragen · Intermediate
Multiple choice
See the testProgrammeervaardighedenPySpark
10 minuten · 15 vragen · Intermediate
Multiple choice
See the testSoftwarevaardighedenSnowflake
10 minuten · 15 vragen · Intermediate
Multiple choice
See the testSoftwarevaardighedenTableau
10 minuten · 15 vragen · Intermediate
Multiple choice
See the testFunctiegebonden vaardighedenWorking With Data
10 minuten · 12 vragen · Intermediate
Multiple choice
See the testTests by category
- Functiegebonden vaardigheden (9 tests)
- Programmeervaardigheden (7 tests)
- Softwarevaardigheden (6 tests)
What data and analytics tests cover
The 22 tests focus on intermediate skills across the data workflow. For statistical reasoning and interpreting patterns, consider Fundamentals of Statistics and Probability or Exploratory Data Analysis. Data Science covers statistical reasoning, data wrangling in code, machine learning modeling, and neural network training.
For preparing datasets, Data Wrangling assesses parsing, cleaning, reshaping, joining, and checking data. Data Extraction, Transformation, and Loading (ETL) focuses on designing and running loads, checking output, and pipeline reliability. Data Modeling Concepts covers relationships, keys, normalization, and models at conceptual, logical, and physical levels.
Other tests address a named language, library or platform. Single Python libraries have their own tests, such as NumPy for arrays and Matplotlib for plotting. Snowflake covers the warehouse's design, SQL, data loading and performance tuning. Other tests focus on interpreting data and communicating decisions, including Data-Driven Decision Making and Data Storytelling. Each test takes 10 minutes, except Pandas, which takes 12 minutes. All use multiple-choice questions.
Choose tests for the role’s work
Match the assessment to the tasks and tools named for the role. For data engineers and analytics engineers building or maintaining Spark pipelines, Apache Spark for Data Engineers assesses Spark jobs, DataFrame transformations, tuning, and streaming. PySpark suits roles that need intermediate PySpark skills, including data engineers, data scientists, and analysts. For Python work with tabular data, Pandas measures reading and writing code to select, clean, combine, and summarize data.
For analysts who prepare or analyze data on a particular cloud platform, choose the matching assessment: Data Analytics in Amazon Web Services (AWS), Data Analytics in Azure, or Data Analytics in Google Cloud Platform (GCP). Each is intended for intermediate-level work with that platform’s analytics services.
For reporting roles, Power BI assesses the service, Power Query, data models, DAX, and report visuals. Tableau covers data preparation, calculations, charts, and interactive dashboards. For roles turning spreadsheet data into figures and charts, Data Analytics in Excel is a direct fit. These tests are intermediate, so select them when the role calls for that level and the named work.
Combine assessments around the job
Use a small set of tests that covers distinct parts of the role, rather than several assessments of the same task. A data analyst role that explores datasets and presents findings might combine Exploratory Data Analysis with Data Storytelling. If the job also uses a named reporting tool, add the relevant assessment, such as Power BI or Tableau, rather than testing unrelated platforms.
For a data engineer working with pipelines, pair Data Wrangling with the relevant ETL or Spark test. Add Data Modeling Concepts if the role also designs or reviews data structures. A role that uses data to guide business choices may call for Data-Driven Decision Making, while a role that builds models may call for Data Science or Fundamentals of Statistics and Probability.
These are all intermediate assessments, so they do not distinguish beginner from advanced levels. Keep the combination tied to the specific work and tools the role requires. Review each result as evidence about the skills it measures, alongside the rest of the hiring process. A score is a signal for a person to consider, not a pass mark or a decision on its own.
Fairness in the questions
The tests use different safeguards suited to their content. Many use neutral examples such as orders, sensor readings, shipments, visits, or survey answers, with names from many backgrounds. Questions avoid money symbols, idioms, sports, and local knowledge where those details are not needed. Plain wording helps keep the focus on the skill being assessed rather than English fluency or reading speed.
Code-focused assessments use short snippets and aim to avoid behavior that varies across software versions or products. Some state settings or behavior a question depends on. Data Analysis Using R shows each small dataset within the question, while Google Cloud questions include needed tables, queries, or statistics. Questions about statistics explain notation where used and provide any table values needed. Charts and visual questions use labels, values, markers, patterns, or line styles rather than relying on color alone.
Practical access details vary by test. Several tests, including ETL and R, allow scratch paper for every candidate. Fundamentals of Statistics and Probability and Working With Data also give every candidate a calculator. Excel, Power BI, and Tableau ask candidates to use a computer so charts and tables are large enough to read. Check the individual test details when choosing assessments, and interpret each result in context.
Veelgestelde vragen
Which data and analytics tests suit a data analyst role?+
Choose based on the role’s work. Exploratory Data Analysis assesses reading and summarizing data with statistics and charts. Data Wrangling covers preparing data, while Data Storytelling focuses on charts, visuals, findings, and decisions. Add a tool test only when the job uses that tool, such as Power BI or Tableau for dashboards, or Data Analysis Using R for analysis in R.
Are the data and analytics assessment tests for beginner or advanced levels?+
All 22 tests are set at an intermediate level, and none has a beginner or advanced version. For data entry or data assistant roles, Working With Data is the closest fit: it covers keeping data clean and consistent, basic analysis and reading charts.
How should employers combine data and analytics tests?+
Choose assessments that cover separate responsibilities in the role. For example, an analyst who explores data and presents findings could take Exploratory Data Analysis and Data Storytelling. For pipeline work, combine a relevant ETL or Spark assessment with Data Wrangling, and add Data Modeling Concepts when modeling is part of the job.
Which data tests need no knowledge of a particular software tool?+
Data-Driven Decision Making needs no knowledge of a particular software tool, and Data Storytelling names no specific software. Exploratory Data Analysis shows no code, and Working With Data needs no tool or product knowledge. These suit roles where the tool varies, while the platform tests suit roles tied to one named product.
How long do the data and analytics tests take?+
Each test takes 10 minutes, except Pandas, which takes 12. All use multiple-choice questions, and a set of three takes about 30 to 32 minutes. Five tests ask for a computer rather than a phone, among them Pandas and Data Analysis Using R.
How do data and analytics tests account for fairness?+
The fairness details differ by assessment, but many use neutral data and plain wording, and avoid unnecessary local or cultural knowledge. Charts are described or labeled so answers do not depend on color alone. Several tests allow scratch paper for every candidate, and the statistics test provides an on-screen calculator.
Build an assessment from these tests
Pick the tests for your role, invite candidates and compare their results.