.png){kind=logo}
AIDA 181 - Big Data Analytics for Risk and Insurance Exam Prep| Questions and Verified Answers| 100% Correct (Latest 2026/2027 Update)
AIDA 181 - Big Data Analytics for Risk and
Insurance Exam Prep| Questions and
Verified Answers| 100% Correct (Latest
2026/2027 Update)
Q: machine learning
Answer:
AI in which computers continually teach themselves to make better decisions on previous results
and new data
Q: Artificial intelligence
Answer:
compute processing/output that simulates reasoning or knowledge
Q: why do tech companies use AI
Answer:
Tech companies use this to "Solve problems or to introduce new products"
Q: data science
Answer:
An interdisciplinary field involving the design and use of techniques to process very large
amounts of data from a variety of sources and to provide knowledge based on the data
Q: structured data
example
Answer:
data organized into databases with defined fields, including links between databases
Microsoft Access
Q: unstructured data
Answer:
Data that is not organized into predetermined formats. Such as databases, and often consists of
texts, images, or other nontraditional media
Q: internal data
examples
Answer:
data that is owned by an organization
premium records, adjuster photos
Q: external data
Answer:
Data that belongs to an entity other than the organization that wishes to acquire and use it
Q: describe economic data in terms of external data
Answer:
Data regarding interest rates, asset prices, exchange rates, the Consumer Price Index, and other
information about the global, the national or a regional economy
Q: geodemographic data
Answer:
data regarding classifications of a population
Q: what is the motto for data quality
Answer:
garbage in - garbage out
Q: list some examples of typical data quality problems
Answer:
missing data / NULL values
duplicate records
default values rather then actual values
Q: ways to detect data quality problems
Answer:
descriptive statistics
data cubes
Q: descriptive statistics
Answer:
Qualitative summaries of the characteristics of a data set, such as the total or average
Q: data cubes
Answer:
A multidimensional partitioning of data into two or more categories
Q: metadata
Answer:
data about the data that provides context for analyzing transaction facts with efficient structures
for grouping hierarchical information
Q: what type of data helps prevent data quality issues?
Answer:
metadata
Q: what are some data mining techniques
Answer:
classification
regression analysis
association rule learning
cluster analysis
.png)