VL 1.1 Business Analytics: Big Data & Statistics
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Questions and Answers

Descriptive Statistics involves using machine learning techniques to identify future outcomes.

False

Prescriptive Statistics analyzes past performance and trends to determine future actions.

True

Big Data Analytics only refers to the high volume of data, not data types and structures.

False

Predictive Statistics focuses on identifying the likelihood of future outcomes based on historical data.

<p>True</p> Signup and view all the answers

The main purpose of Big Data Analytics is to provide historical data insights only.

<p>False</p> Signup and view all the answers

Decision Trees are an example of Descriptive Statistics techniques.

<p>False</p> Signup and view all the answers

As data type becomes more disorderly, less data preparation or pre-processing time is required.

<p>False</p> Signup and view all the answers

Semi-structured data can be easily addressed by using parsing, a function available in Excel.

<p>True</p> Signup and view all the answers

Quasi-structured data is defined as having consistent and easily interpretable formats.

<p>False</p> Signup and view all the answers

Parsing semi-structured data may lead to issues if the data is not well-organized.

<p>False</p> Signup and view all the answers

Successful parsing of semi-structured data allows for proper processing of the data.

<p>True</p> Signup and view all the answers

Quasi-structured data requires no additional effort for formatting and can be easily handled.

<p>False</p> Signup and view all the answers

Cropital is a healthcare-focused crowdfunding platform that uses Big Data to assess the creditworthiness of potential borrowers.

<p>False</p> Signup and view all the answers

Financial institutions purchase data from data collectors and aggregators to optimize pricing strategies.

<p>False</p> Signup and view all the answers

Statista collects data on topics such as consumer behavior, industry trends, and market research.

<p>True</p> Signup and view all the answers

Retailers purchase data from data aggregators to assess credit risk.

<p>False</p> Signup and view all the answers

Marketing agencies purchase data from data aggregators to develop personalized financial products.

<p>False</p> Signup and view all the answers

Data Users/Buyers are entities that collect data on consumer behavior, industry trends, and market research.

<p>False</p> Signup and view all the answers

Data profiling involves examining tables, files, and database structure before the extraction process.

<p>True</p> Signup and view all the answers

Failure during the ETL process is impossible if the data is considered 'Too Dirty'.

<p>False</p> Signup and view all the answers

Incorrect relationships between tables are examples of data quality issues related to database structures.

<p>True</p> Signup and view all the answers

Data quality issues related to having two or more files about a single subject, with mismatched unique identifiers, are common in the ordering process.

<p>False</p> Signup and view all the answers

Intervention to address data quality issues includes reviewing the source details manually and making corrections as necessary.

<p>True</p> Signup and view all the answers

Conducting data gathering is the first step in the Extract-Transform-Load (ETL) process.

<p>False</p> Signup and view all the answers

A perceptron is a plane that maximizes the margin between two classes.

<p>False</p> Signup and view all the answers

Support Vectors are equivalent to two lines at the edge of a plane.

<p>False</p> Signup and view all the answers

The perceptron separates classes in a non-parametric way.

<p>True</p> Signup and view all the answers

The perceptron is used to determine the class of any particular dot based on its position relative to the line.

<p>True</p> Signup and view all the answers

Default values classified as 'yes' are represented by negative numbers relative to the perceptron.

<p>False</p> Signup and view all the answers

Pre-processing of data involves plotting distance normalized values after normalization.

<p>False</p> Signup and view all the answers

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