Course 1 Week 2 - All About Analytical Thinking
5 aspects of analytical thinking
1) Visualization - graphical representation of info 2) Strategy - what want to achieve and how they are going to get there 3) Problem-orientation - use to ID, describe and solve problems 4) Correlation - relationship between 2 pieces of data 5) Big-picture and detail-oriented thinking - zoom out and see possibilities and opportunities & figuring out all of the small aspects
5 key data analyst skills
1) curiosity 2) understanding context - listens and understanding full picture 3) having a technical mindset - ability to break things down into smaller steps or pieces and work with them in an orderly and logical way 4) data design - how you organize information 5) data strategy - management of the people, processes and tools used in data analysis
Curiosity
A junior data analyst is seeking out new experiences in order to gain knowledge. They watch videos and read articles about data analytics. They ask experts questions. Which analytical skill are they using?
Gap analysis
A method for examining and evaluating the current state of a process in order to identify opportunities for improvement in the future
Understanding context
Identifying the motivation behind data collection and gathering additional information are examples of which analytical skill?
Data strategy
In data analysis, which analytical skill involves the management of people, processes, and tools?
Analytical skills
Qualities and characteristics associated with using facts to solve problems
A technical mindset
Fill in the blank: _____ involves the ability to break things down into smaller steps or pieces and work with them in an orderly and logical way
Data design
How information is organized
Context
The condition in which something exists or happens
Data visualization
The graphical representation of data
Data strategy
The management of the people, processes, and tools used in data analysis
Analytical thinking
The process of identifying and defining a problem, then solving it by using data in an organized, step-by-step manner
Root cause
The reason why a problem occurs
Dataset
A collection of data that can be manipulated or analyzed as one unit
analytical skills
Fill in the blank: Curiosity, understanding context, and having a technical mindset are all examples of _____ used in data-driven decision-making
False
T/F: Correlation is the aspect of analytical thinking that involves figuring out the specifics that help you execute a plan
True
T/F: Data analysts ask, "Why?" five times in order to get to the root cause of a problem.
True
T/F: Data design is how you organize information; data strategy is the management of the people, processes, and tools used in data analysis.
True
T/F: Data-driven decision-making involves the five analytical skills: curiosity, understanding context, having a technical mindset, data design, and data strategy. Each plays a role in data-driven decision-making
True
T/F: Gap analysis is a method for examining and evaluating how a process works currently in order to get where you want to be in the future
True
T/F: Gap analysis is used to examine and evaluate how a process currently works with the goal of getting to where you want to be in the future
True
T/F: Surveying customers about their preferences and using that information to inform business strategy is an example of data-driven decision-making
Technical mindset
The ability to break things down into smaller steps or pieces and work with them in an orderly and logical way
Analytical thinking
What practice involves identifying, defining, and solving a problem by using data in an organized, step-by-step manner?
Correlation
Which aspect of analytical thinking involves being able to identify a relationship between two or more pieces of data?
