Audit Data Analytics

Question 1

What is a bit?

Answer 1

A bit is a single switch in a computer that is either in the on (1) or off (0) position.

Question 2

What is a byte?

Answer 2

A byte is a group of 8 bits that represents a character.

Question 3

What is a field?

Answer 3

A field is a group of related characters that represents a unit of information. For example, a field in a database might be the name of a person of the date of birth.

Question 4

What is a record?

Answer 4

A record is a group of logically related fields that represent a complete unit of information.
A record can be searched in a file using a Primary Key or a Secondary Key.

Question 5

What is a primary key?

Answer 5

A primary key is a field in a record that can be used to uniquely identify that record.

Question 6

What is a secondary key?

Answer 6

A secondary key is a key that can be used to locate a record in the database when the primary key is unknown.

Question 7

What is a foreign key?

Answer 7

A foreign key is a column or set of columns in a relational database table that is used to establish and maintain a link between the data in two tables.

Question 8

What is a file?

Answer 8

A file is a group of logically related records. Files can contain a variety of types of data, including test, images, audio, and video.

Question 9

What is a master file?

Answer 9

A master file typically contains information that is not expected to change frequently, such as customer data, product data, or vendor data.

Question 10

What is a detail file?

Answer 10

A detail file is a file that lists a group of transactions, such as sales orders, invoices, or purchase orders.

Question 11

What is a database?

Answer 11

A database is a collection of logically related files that are organized and stored in a computer and are devoted to a common function.

Question 12

What is a relational database?

Answer 12

A relational database is based on the relational model, where data is organized into tables (relations) consisting of rows (tuples) and columns (attributes).
Tables are related to each other using primary and foreign keys, allowing for the representation of complex relationships between entities.

Question 13

What are examples of tabular format?

Answer 13

Excel or CSV files.

Question 14

What are formats of data?

Answer 14

Tabular format
Database format
Raw text format
API output format

Question 15

What are examples of data sources?

Answer 15

Internal databases
External sources
File repositories
Web services or APIs
Physical documents

Question 16

What are data quality and cleansing requirements?

Answer 16

This may include removing duplicates, handling missing values, or ensuring data consistency.

Question 17

What are legal and ethical considerations?

Answer 17

If sensitive personal data is involved, obtain the necessary permissions and safeguards.

Question 18

What should be considered for documentation and traceability?

Answer 18

Maintain detailed documentation of your data extraction request, including the requestor’s name, purpose, attributes, sources, and any transformations applied.

Question 19

What are types of data transformation?

Answer 19

Data cleaning
Data standardization
Data encoding
Data aggregation and grouping
Data transformation and scaling
Data merging and joining
Data deduplication
Time-series data handling
Text data processing
Data quality checks
Documentation and logging
Test data transformation scripts
Automation
Validation and verification

Question 20

Automated tools and techniques to process data

Answer 20

Define your objectives
Select the right tools
Data acquisition
Data cleaning and preprocessing
Data transformation and structuring
Data analysis and modeling
Visualization and reporting
Automation scripts and workflows
Validate results
Document the process
Review and quality assurance
Interpretation and contextualization
Use as evidence
Maintain data security and privacy
Continuous improvements

Question 21

What are measurement scales of data?

Answer 21

Nominal scale
Ordinal scale
Interval scale
Ratio scale
Continuous data
Discrete data

Question 22

What is a nominal scale?

Answer 22

Nominal scales represent data with categories that have a meaningful order or ranking, but the intervals between categories are not necessarily equal.

Question 23

What is an ordinal scale?

Answer 23

Ordinal scales represent data with categories that have a meaningful order or ranking, but the intervals between categories are not necessarily equal.

Question 24

What is an interval scale?

Answer 24

Interval scales represent data with categories that have a meaningful order, and the intervals between categories are equal. There is no zero point.

Question 25

What is a ratio scale?

Answer 25

Ratio scales are similar to interval scales but have a true zero point, indicating the absence of the attribute being measured. Rations have meaningful and equal intervals.

Question 26

What is continuous data?

Answer 26

Continuous data can take any value within a range and often involve measurements on a ratio or interval scale.

Question 27

What is discrete data?

Answer 27

Discrete data consist of distinct, separate values with no values in between.

Question 28

What audit activities use data analytics?

Answer 28

Analyze risks
Test controls
Assist in analytical procedures
Support judgements
Provide insights

Question 29

What are examples of use of data analytics in audit?

Answer 29

Analyzing trends in revenues
Scrutinizing inventory
Examining 100% transactions
Fraud detection
Expense analysis
Test of revenue recognition
Vendor and supplier audit
Tax compliance
Internal controls testing
Customer and account reconciliation

Question 30

What are steps to applying audit data analytics?

Answer 30

Plan (objective planning, data selection, tool and technique selection)
Access and prepare the data
Assess relevance and reliability
Perform audit data analytics
Evaluate and conclude

Question 31

What are benefits of audit data analytics?

Answer 31

Enhanced efficiency
Increased accuracy
Improved risk assessment
Enhanced audit quality
Better control testing
Valuable business insights
Increased client satisfaction
Enhanced fraud detection
Flexible and scalable

Question 32

What are challenges and considerations in applying audit data analytics?

Answer 32

Data quality
Data security
Skillset
Regulatory compliance