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Business Intelligence & Data Analytics Free Online Certification

Business Intelligence & Data Analytics Free Online Certification

Get Business Intelligence & Data Analytics Certificate from MachineLearning.org.in which you can share in the Certifications section of your LinkedIn profile, on printed resumes, CVs, or other documents.

Exam Details

  • Format: Multiple Choice Question
  • Questions: 10
  • Passing Score: 8/10 or 80%
  • Language: English

Skills you will learn : Data Transformation, Automation, Visualization, Modeling, Coding, Predictive Analysis, Statistics, and more

Career paths after completing the quiz : Data Analyst, Business Analyst, Data Scientist, BI Developer, Data Visualization Analyst, and more

Here are the questions and answers :

_ is the outcome of extraction and processing activities carried out on data.

Knowledge
Information
Data
Raw Data

The objective of Business Intelligence is

To support decision-making and complex problem solving.
To support information gathering.
To support data collection.
To support data analysis.

Which of the following is not a component of business intelligence analysis cycle?

Analysis
Insight
Decision
Design

In BI Architecture, It is used to gather and integrate the data stored in various primary and secondary sources.

Data Warehouse
Data mart
Data Sources
None of the above

Following are the phases of Development of a business intelligence system.

Analysis and Design
Planning
Implementation and Control
All of the above

How the customer satisfaction can be achieved

By gathering, storing, analysing and understanding huge of customer data
Implementaion of dataware house
Giving them discount
Interaction

Regression is the type of ______________ learning

Supervised learning
Unsupervised learning
Reinforcement learning
Semi-supervised

__________is an essential process where intelligent methods are applied to extract data patterns

Dataware housing
Data mining
Database
Data structure

The technique of finding hidden structure in unlabeled data is called

Supervised learning
Unsupervised learning
Reinforcement learning
Deep learnng

The bank wants to segment their customer into distinct group to give loan offer, this is an example of:

Supervised learning
Data extraction
Unsupervised learning
Data preprocessing

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