Midterm Exam #1 Flashcards
What are the eleven leadership topics we’ve covered in class?
Careful! Even gross germs in M&Ms pass prior PNVs.
communication
effectiveness
gratitude
good days
influence
motivation
momentum
passion
priorities
process and navigation
vision
The process of transforming data into insights to improve business decisions is…
business analytics
Descriptive analytics is also known as…
exploratory data analytics
This type of analytics includes the interpretation of historical data to identify trends and patterns.
descriptive analytics
This type of analytics includes the use of statistics to forecast future outcomes.
predictive analytics
This type of analytics includes the application of testing and other techniques to determine which outcome will yield the best result in a given scenario.
prescriptive analytics
What is the “big idea?”
- the most interesting idea
- one sentence
- client must continue looking into it
This is the complete set of data, with all possible values taken into consideration.
population
This is a section or subset of data used for analysis.
sample
Sample data can either be…
randomized
stratified
What does it mean when a population sample is determined through “stratification?”
based on some rules of interest
QUALITATIVE data refers to…
categorical, or non-numeric, data
QUANTITATIVE data refers to…
numeric data
What are the two types of qualitative data?
nominal and ordinal
What are the two types of quantitative data?
discrete and continuous
Nominal data falls under (qual-/quant-), and it is used for…
qualitative data
named categories
examples: colors, gender
Ordinal data falls under (qual-/quant-), and it is used for…
qualitative data
intrinsically-ordered things you can’t add up
examples: satisfaction ranking, medals, education level
Discrete data falls under (qual-/quant-), and it is used for…
quantitative data
exact numbers only
examples: number of people, number of cars
Continuous data falls under (qual-/quant-), and it is used for…
quantitative data
can be in ranges
examples: height, weight, distance
___________ are usually the result of long-term factors such as population, refers to the general direction in which something is changing.
trends
___________ are repeated occurrences or sequences.
patterns
___________ are connections or associations between concepts or ideas; what learning about one variable tells you about the other.
relationships
What are the steps in the analytics process?
I-I say, Claire there’s an intricate model.
identify the business problem
identify the data sources
select the data
clean the data
transform the data
analyze the data
interpret + deploy model
The process of fixing incorrect, incomplete, duplicate or otherwise erroneous data in a data set is…
data cleansing
The process of converting and structuring data into a usable format that can be analyzed is…
data transforming
In Power BI, these are visual representations of an enterprise’s data elements and the connections between them.
data models
A lookup table / dimension table holds ________ values.
unique!
A data table holds _________ values.
nonunique!
A lookup table / dimension table has ___________ keys.
primary
A data table has ___________ keys.
foreign
The process of organizing the tables and columns in one database to reduce redundancy and preserve data integrity is…
normalization
In Power BI, the term ‘DAX’ stands for…
Data Analysis Expressions
What are DAXs?
- they are like excel formulas for Power BI
- they primarily are used for relational data
Within power query, where do you access the source to re-link files when they have been moved?
Query settings –> Applied Steps –> Source
Power query is used to…
- clean data
- transform data
- organize data
Power query is NOT used to…
ANALYZE data
All of the following data types are used in Power Query except:
- percentage
- string
- whole number
- text
string
What is SQL?
It stands for “structure query language.”
It is:
- used to communicate with a database
- the standard language for relational database management systems
- more coding focused
Name examples of data cleansing in Power BI.
edit query names
change data types
edit column names (uppercase, lowercase)
Data Type: Correct data type
Remove null/blank columns and rows
append data
moving columns
Name examples of data transforming in Power BI.
Fixing Data Source Errors, Broken Links, & Files
Index columns
Merging columns
Splitting columns
Custom columns
relinking columns
merge queries
adding new rows
deleting rows
What is the MVP?
minimum viable plan
Why is creating Relationships between tables important when using Power BI?
Relationships join tables together so that you can build a Matrix Visualization using fields from multiple tables.
