Clock
Test duration:
20
min
Notes
No. of questions:
10
Tie
Level of experience:
Mid

SSAS Test 2008

SSAS 2008 online assessment test is the ideal pre-employment assessment for recruiters to assess SSAS skills of the candidates before the interview. This test has helped our customers reduce their hiring costs and time-to-hire by 40%.

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About

SSAS 2008 Online Assessment Test

Microsoft SQL Server Analysis Services (SSAS) is an online analytical processing (OLAP) and data mining tool in Microsoft SQL Server. This tool is used to analyze and make sense of information possibly spread out across multiple databases, or in disparate tables or files.

SSAS 2008 online assessment test helps recruiters and hiring managers to evaluate SSAS skills of the candidate. SSAS 2008 development test is designed and validated by Subject Matter Experts (SME) to assess and hire SSAS developer as per the industry standard.

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How it works

Test Summary

Recruiters can use intelligent and powerful test insights that will help to identify job fit candidates more accurately with score distribution  and section analysis features. SSAS 2008 online assessment test is designed considering EEOC guidelines, it will help you assess & hire diverse talent without any bias.

This test may contain MCQs (Multiple Choice Questions), MAQs (Multiple Answer Questions), Fill in the Blanks, Whiteboard Questions, Audio / Video Questions, AI-LogicBox , Coding Simulators, True or False Questions, etc.

Test Duration
20
No. of Questions
10
Level of Expertise
Mid
Useful for hiring
  • SSAS Developer
  • SQL Server BI Developer
  • SSAS BI Consultant
Topics Covered
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Development

Our SSAS 2008 online assessment test helps recruiters to evaluate candidates SSAS development skills

Security

This SSAS test helps recruiters to assess candidates&
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Deployment

Our SSAS development test helps recruiters to evaluate candidates&
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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:

Difficulty:

Easy

Question:

You create a SQL Server 2008 Analysis Services (SSAS) solution. The solution contains a time dimension named DimTime. You have a table named FactSales that contains two columns named OrderDate and ShipDate. The two columns refer to the DimTime dimension. You need to ensure that the DimTime dimension can be used to browse through measures in the FactSales table for both OrderDate and ShipDate. What should you do?


Options

  • Create a reference relationship between the DimTime dimension and the FactSales measure group.
  • Create a many-to-many relationship between the DimTime dimension and the FactSales measure group.
  • Create two regular relationships between the DimTime dimension and the FactSales measure group. Use identical measure group columns.
  • Create two regular relationships between the DimTime dimension and the FactSales measure group. Use different measure group columns.
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FAQ
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