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Google Data Studio Online Test
Clock
Test duration:
20
min
Notes
No. of questions:
10
Tie
Level of experience:
Entry/Mid/Senior

Google Data Studio Test

Our Google Data Studio online test is the ideal pre-employment assessment for recruiters & hiring managers to assess candidates' proficiency in data visualization and analytical skills. This test assesses candidates' knowledge of topics like pivot charts, data studio filters, and reports. This test has helped our customers reduce their hiring costs and time-to-hire by 45%.

13654
+
Candidates
Assessed
132
+
Organizations Served
Fujitsu
Paypal
Capgemini
Deloitte
Coupa
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About

Google Data Studio Online Test

Google Data Studio turns data into informative reports and interactive dashboards that are easy to read and share and are fully customizable for your business intelligence needs. Google Data Studio can connect to a variety of data sources, including Google Analytics. You can also upload your Excel data using the CSV format.

The Google Data Studio online test helps employers to assess candidates' Google Data Studio analytical skills. The Google Data Studio skills test is designed & validated by experienced Subject Matter Experts (SMEs) to assess and hire Google Data Studio Experts per industry standards.

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How it works

Test Summary

The Google Data Studio skills test helps to screen the candidates who possess the following traits:

  • Experience with data visualization pivot charts in Google Data Studio.
  • Knowledge of Google Data Studio filters for retrieving various records.
  • Good understanding of Google Data Studio reports and data sorts.
  • Familiarity with concepts like bullet charts, data control, etc., in Google Data Studio

Using powerful reporting, you can have a detailed analysis of our test results to make a better hiring decision and predict candidates' performance. To know about candidates' experience, we have introduced a new feature called the 'candidate feedback module' in our Google Data Studio online test, so you can ensure that candidates are getting an excellent experience while attempting the test.   

  

The Google Data Studio skills test may contain MCQs (Multiple Choice Questions), MAQs (Multiple Answer Questions), Fill in the Blanks, Whiteboard Questions, Audio/Video Questions, AI-LogicBox (AI-based essay evaluation), Job-based Simulations, True or False Questions, etc.

Test Duration
20
No. of Questions
10
Level of Expertise
Entry/Mid/Senior
Useful for hiring
  • Google Data Studio Application Developer
  • Data Scientist
  • Data Analyst
  • Dashboard Expert
Topics Covered
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Data Visualization - Pivot Table

The Google Data Studio online test helps recruiters to evaluate a candidate's proficiency in using pivot tables to cut, slice, summarize, derive meaningful results from the data, and present the data graphically.

Google Data Studio Report

This assessment helps recruiters to assess a candidate's skills in working with Google Data Studio reports.
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Google Data Studio Filters

The Google Data Studio skills test quantifies a candidate's ability to work with Google Data Studio filters, which are very similar to filters in Google Analytics.
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Data Visualization - Bullet Chart

This assessment helps to evaluate a candidate's knowledge of using bullet charts to visually track performance against a target and display results in a single column.
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Sample Question
Choose from our 100,000+ questions library or add your own questions to make powerful custom tests.

Question types :

Multiple Option

Topic:

Difficulty:

Hard


Q 1. You have been asked to train « Naive Bayes model for spam detection dataset

Using Python command, what wil you add in the given code at XXXX to deciore, it and train your modal for the given dataset?

import numpy os np

X= nporroyll 3. 2b[1 21 [2.21.[3,21)
Y= nporray(fi.a,a.1))

XXXX

from skinamnaive_bayas import

Gaussianna

otf = Gaussianne()

ceataie(x ¥)

from skinamnaive_bayas import

Gaussianna

otf = Gaussianne()

ceataie(x ¥)

from skinamnaive_bayas import

Gaussianna

otf = Gaussianne()

ceataie(x ¥)

from skinamnaive_bayas import

Gaussianna

otf = Gaussianne()

ceataie(x ¥)

Question types :

Multiple Option

Topic:

Machine teaming

Difficulty:

Hard


Q 1. Q2 Lets assume that you have 6 Pandas DataFrome(af) in the below tole.

Index Code Open High
0 AAPL 19877 70074
1 AAPL 19877 70074
2 AAPL 19877 70074
3 AAPL 19877 70074
4 AAPL 19877 70074

When the following commend is executed, what hoppens to the DatoFrome?

df= defiinat()
Y= nporray(fi.a,a.1))

Index Code Open High
0 AAPL 19877 70074
1 AAPL 19877 70074
2 AAPL 19877 70074
3 AAPL 19877 70074
4 AAPL 19877 70074
Index Code Open High
0 AAPL 19877 70074
1 AAPL 19877 70074
2 AAPL 19877 70074
3 AAPL 19877 70074
4 AAPL 19877 70074
it gives an error becouse of the third row which has on empty string.
None of these

Question types :

Multiple Option

Topic:

Data Visualisation - Column chart

Difficulty:

Easy

Question:

You want to visualize the product sales per month using a column chart. You can do that by:


Options

  • Click Add a chart - Select column chart model - Select products fields - Select Sales fields
  • Click Add a chart - Select column chart model - Drag sales field into metrics
  • Click Add a chart - Select column chart model - Drag products field into metrics
  • Click Add a chart - Select column chart model - Drag sales field into dimension
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FAQ
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