WGU C207 – DATA-DRIVEN DECISION-MAKING
EXAM QUESTIONS AND FULLY CORRECT
ANSWERS RECENTLY UPDATED
300 QUESTIONS AND ANSWERS
1. What is data-driven decision making? The process of making
organizational decisions based on actual data rather than intuition or observation
alone.
2. What are the key components of data-driven decision making? Data
collection, analysis, interpretation, and application to business decisions.
3. What is the difference between data, information, and knowledge? Data
is raw facts, information is processed data, and knowledge is information
applied with experience and context.
4. What are the main types of data? Quantitative (numerical) and qualitative
(categorical/descriptive) data.
5. What is structured data? Data that is organized in a predefined format,
typically in rows and columns like databases or spreadsheets.
6. What is unstructured data? Data that doesn't have a predefined format,
such as text documents, images, videos, or social media posts.
7. What is semi-structured data? Data that has some organizational properties
but doesn't conform to a rigid structure, like JSON or XML files.
8. What are the four V's of Big Data? Volume, Velocity, Variety, and
Veracity.
9. What does Volume refer to in Big Data? The amount or size of data being
generated and collected.
,10. What does Velocity refer to in Big Data? The speed at which data is
generated, collected, and processed.
11. What does Variety refer to in Big Data? The different types and formats
of data from various sources.
12. What does Veracity refer to in Big Data? The accuracy, reliability, and
quality of the data.
13. What is a data warehouse? A central repository that stores integrated data
from multiple sources for analysis and reporting.
14. What is a data mart? A subset of a data warehouse that focuses on a
specific business area or department.
15. What is ETL in data processing? Extract, Transform, Load - the process
of extracting data from sources, transforming it into a usable format, and
loading it into a target system.
16. What is data mining? The process of discovering patterns, correlations,
and insights from large datasets using statistical and machine learning
techniques.
17. What is business intelligence (BI)? Technologies and practices for
collecting, analyzing, and presenting business data to support decision-making.
18. What is a key performance indicator (KPI)? A measurable value that
indicates how effectively an organization is achieving its key objectives.
19. What is a dashboard in business intelligence? A visual display of key
metrics and data points relevant to achieving business objectives.
20. What is data governance? The overall management of data availability,
usability, integrity, and security within an organization.
21. What are the main benefits of data-driven decision making? Improved
accuracy, reduced bias, better risk management, increased efficiency, and
competitive advantage.
22. What are common barriers to data-driven decision making? Poor data
quality, lack of skills, organizational resistance, insufficient technology, and
data silos.
23. What is data quality? The degree to which data is accurate, complete,
consistent, timely, and relevant for its intended use.
, 24. What are the dimensions of data quality? Accuracy, completeness,
consistency, timeliness, validity, and uniqueness.
25. What is data cleansing? The process of identifying and correcting errors,
inconsistencies, and inaccuracies in data.
26. What is data integration? The process of combining data from different
sources to provide a unified view.
27. What is a data model? A conceptual representation of data structures and
relationships within a system.
28. What is metadata? Data about data - information that describes the
characteristics of other data.
29. What is data lineage? The complete journey of data from its origin to its
final destination, including all transformations.
30. What is master data management (MDM)? The practice of managing and
maintaining consistent, accurate master data across an organization.
31. What is predictive analytics? The use of statistical algorithms and machine
learning techniques to identify future outcomes based on historical data.
32. What is descriptive analytics? The analysis of historical data to understand
what has happened in the past.
33. What is prescriptive analytics? Analytics that recommends actions based
on data analysis and prediction models.
34. What is diagnostic analytics? Analytics that examines data to understand
why something happened.
35. What is real-time analytics? The analysis of data as it is created or
received, enabling immediate insights and responses.
36. What is batch processing? Processing data in large blocks or batches at
scheduled intervals.
37. What is stream processing? Processing data continuously as it flows
through a system in real-time.
38. What is a data lake? A storage repository that holds vast amounts of raw
data in its native format until needed.
EXAM QUESTIONS AND FULLY CORRECT
ANSWERS RECENTLY UPDATED
300 QUESTIONS AND ANSWERS
1. What is data-driven decision making? The process of making
organizational decisions based on actual data rather than intuition or observation
alone.
2. What are the key components of data-driven decision making? Data
collection, analysis, interpretation, and application to business decisions.
3. What is the difference between data, information, and knowledge? Data
is raw facts, information is processed data, and knowledge is information
applied with experience and context.
4. What are the main types of data? Quantitative (numerical) and qualitative
(categorical/descriptive) data.
5. What is structured data? Data that is organized in a predefined format,
typically in rows and columns like databases or spreadsheets.
6. What is unstructured data? Data that doesn't have a predefined format,
such as text documents, images, videos, or social media posts.
7. What is semi-structured data? Data that has some organizational properties
but doesn't conform to a rigid structure, like JSON or XML files.
8. What are the four V's of Big Data? Volume, Velocity, Variety, and
Veracity.
9. What does Volume refer to in Big Data? The amount or size of data being
generated and collected.
,10. What does Velocity refer to in Big Data? The speed at which data is
generated, collected, and processed.
11. What does Variety refer to in Big Data? The different types and formats
of data from various sources.
12. What does Veracity refer to in Big Data? The accuracy, reliability, and
quality of the data.
13. What is a data warehouse? A central repository that stores integrated data
from multiple sources for analysis and reporting.
14. What is a data mart? A subset of a data warehouse that focuses on a
specific business area or department.
15. What is ETL in data processing? Extract, Transform, Load - the process
of extracting data from sources, transforming it into a usable format, and
loading it into a target system.
16. What is data mining? The process of discovering patterns, correlations,
and insights from large datasets using statistical and machine learning
techniques.
17. What is business intelligence (BI)? Technologies and practices for
collecting, analyzing, and presenting business data to support decision-making.
18. What is a key performance indicator (KPI)? A measurable value that
indicates how effectively an organization is achieving its key objectives.
19. What is a dashboard in business intelligence? A visual display of key
metrics and data points relevant to achieving business objectives.
20. What is data governance? The overall management of data availability,
usability, integrity, and security within an organization.
21. What are the main benefits of data-driven decision making? Improved
accuracy, reduced bias, better risk management, increased efficiency, and
competitive advantage.
22. What are common barriers to data-driven decision making? Poor data
quality, lack of skills, organizational resistance, insufficient technology, and
data silos.
23. What is data quality? The degree to which data is accurate, complete,
consistent, timely, and relevant for its intended use.
, 24. What are the dimensions of data quality? Accuracy, completeness,
consistency, timeliness, validity, and uniqueness.
25. What is data cleansing? The process of identifying and correcting errors,
inconsistencies, and inaccuracies in data.
26. What is data integration? The process of combining data from different
sources to provide a unified view.
27. What is a data model? A conceptual representation of data structures and
relationships within a system.
28. What is metadata? Data about data - information that describes the
characteristics of other data.
29. What is data lineage? The complete journey of data from its origin to its
final destination, including all transformations.
30. What is master data management (MDM)? The practice of managing and
maintaining consistent, accurate master data across an organization.
31. What is predictive analytics? The use of statistical algorithms and machine
learning techniques to identify future outcomes based on historical data.
32. What is descriptive analytics? The analysis of historical data to understand
what has happened in the past.
33. What is prescriptive analytics? Analytics that recommends actions based
on data analysis and prediction models.
34. What is diagnostic analytics? Analytics that examines data to understand
why something happened.
35. What is real-time analytics? The analysis of data as it is created or
received, enabling immediate insights and responses.
36. What is batch processing? Processing data in large blocks or batches at
scheduled intervals.
37. What is stream processing? Processing data continuously as it flows
through a system in real-time.
38. What is a data lake? A storage repository that holds vast amounts of raw
data in its native format until needed.
