Drag and Drop Matching Questions

Primary Key: Uniquely identifies each record in a table.

A primary key uniquely identifies each record in a table.

Foreign Key: A field that links to the primary key of another table.

A foreign key is a field that references the primary key of another table.

Index: Speeds up data retrieval operations on a table.

An index is used to speed up the retrieval of rows from a table.

Normalization: Process of organizing data to reduce redundancy.

Normalization is a process that removes data redundancy and dependency.

Accuracy: Data correctly reflects real-world values

Accuracy refers to the degree to which data correctly represents the real-world entity or event it is meant to represent.

Completeness: All required data is present

Completeness measures whether all necessary data elements are available and no critical information is missing.

Consistency: Data values are the same across different systems or sources

Consistency ensures that data does not contain contradictions and is uniform when compared across datasets.

Timeliness: Data is available when needed

Timeliness refers to the availability of data at the time required for decision-making or processing.

Simple Random Sampling: Every member of the population has an equal chance of being selected.

This correctly defines simple random sampling, where each individual is selected entirely by chance.

Stratified Sampling: Population is divided into subgroups based on a characteristic, and random samples are drawn from each subgroup.

This correctly describes stratified sampling, ensuring representation from each stratum.

Cluster Sampling: Population is divided into clusters, and entire clusters are randomly selected.

This correctly defines cluster sampling, often used for geographic groupings.

Systematic Sampling: Every kth member is selected from a list after a random start.

This correctly describes systematic sampling, which is easy to implement.

Encryption: Process of converting data into a coded form to prevent unauthorized access.

Encryption is correctly defined as the process of encoding data to protect it from unauthorized access.

Authentication: Process of verifying the identity of a user or system.

Authentication is correctly defined as the process of verifying identity.

Authorization: Process of granting or denying access to resources based on roles.

Authorization is correctly defined as the process of granting or denying access based on permissions.

Non-repudiation: Assurance that a party cannot deny the authenticity of their actions.

Non-repudiation is correctly defined as the assurance that a party cannot deny their actions.

Excel: Spreadsheet analysis and data manipulation

Excel is primarily used for spreadsheet calculations, data organization, and basic analysis.

SQL: Querying and managing relational databases

SQL is designed for retrieving, updating, and managing data in relational databases.

Python: General-purpose programming for data analysis and machine learning

Python is a versatile language used for data manipulation, statistical analysis, and machine learning.

Tableau: Data visualization and business intelligence

Tableau specializes in creating interactive dashboards and visual analytics.

Regression: Predicting a continuous outcome variable based on one or more predictor variables

Regression is used to model the relationship between a dependent variable and independent variables, typically for prediction or forecasting.

Clustering: Grouping a set of objects so that objects in the same group are more similar to each other than to those in other groups

Clustering is an unsupervised learning technique that partitions data into groups based on similarity.

Classification: Assigning a label or category to an observation based on its features

Classification is a supervised learning method that predicts categorical labels for input data.

Principal Component Analysis: Reducing the dimensionality of a dataset while preserving as much variability as possible

PCA is a technique for dimensionality reduction that transforms data into a set of orthogonal components.

Extract: Retrieving data from various source systems

This is the correct definition of the Extract step in ETL.

Transform: Converting data into a suitable format or structure for analysis

This correctly defines the Transform step, which involves cleaning, aggregating, and reformatting data.

Load: Writing transformed data into a target database or data warehouse

This correctly defines the Load step, which involves inserting transformed data into the final destination.