Foundations: Data, Data, Everywhere

Question 1

Name the 6 phases of data analytics

Answer 1

1. Ask
2. Prepare
3. Process
4. Analyse
5. Share
6. Act

Question 2

Describe the ASK phase of data analytics

Answer 2

Trying to understand the challenge to be solved or the key question you are aiming to answer. It is generally assigned to you by stakeholders, but asking many questions can lead to the core question and help along the way.

Question 3

Describe the PREPARE phase of data analytics

Answer 3

Finding and collecting the data needed to answer the key question or other related questions. Data sources need to be identified, the data gathered and verified for accuracy and usefulness.

Question 4

Describe the PROCESS phase of data analytics

Answer 4

Data is cleaned and organised. This involves removing inconsistencies, filling in missing values and, often, changing the data to a more user friendly format.

Question 5

Describe the ANALYSE phase of data analytics

Answer 5

Data is analysed to discover answers and reach solutions. Often we are looking for relationships, patterns and trends, which can be discovered through tasks like calculating averages or counting items in categories.

Question 6

Describe the SHARE phase of data analytics

Answer 6

Presenting findings to decision-makers through a report, presentation or data visualisations. Common data presentation tools include Google Sheets or Microsoft Excel, Tableau, and R.

Question 7

Describe the ACT phase of data analytics

Answer 7

Data insights are put into action by, for example, implementing a new business strategy, making changes to a website, or any other action that solves the initial problem.

Question 8

Define analytical skills

Answer 8

The qualities and characteristics associated with solving problems using facts.

Question 9

What are four key data analysis skills

Answer 9

1. A technical mindset
2. Understanding context
3. Data design
4. Data strategy

Question 10

Define a technical mindset

Answer 10

Having a technical mindset involves breaking processes down into smaller steps and working with them in an orderly, logical way.

Question 11

Define data design

Answer 11

Data design is how you organise information.

Question 12

Define understanding context

Answer 12

Understanding context is understanding the condition in which something exists or happens.

Question 13

Define data strategy

Answer 13

Data strategy involves managing the people, processes and tools used in data analysis. Data strategy gives you a high-level view of the path you need to take to achieve your goals.

Question 14

What is analytical thinking?

Answer 14

Identifying and defining a problem and then solving it by using data in an organised, step-by-step manner.

Question 15

Name the five key aspects to analytical thinking

Answer 15

1. Visualisation
2. Strategy
3. Problem-orientation
4. Correlation
5. Big-picture and detail-oriented thinking

Question 16

Define analytical thinking

Answer 16

Identifying and defining a problem and then solving it by using data in an organised, step-by-step way.

Question 17

Name the five keys to analytical thinking

Answer 17

1. Visualisation
2. Strategy
3. Problem-orientation
4. Correlation
5. Big-picture and detail oriented thinking

Question 18

Define visualisation from a data analytics perspective

Answer 18

The graphical representation of information using graphs, maps and other design elements.

Question 19

Define strategy from a data analytics perspective

Answer 19

Strategising is the zoomed out perspective that helps data analysts see what they want to achieve with the data and how they can get there. It also helps improve the quality and usefulness of the data we collect.

Question 20

Define what it means to be problem oriented from a data analytics perspective

Answer 20

An approach used to identify, describe and solve problems. The aim is to keep the problem top of mind throughout the data analysis process.

Question 21

Define correlation from a data analytics perspective

Answer 21

Correlation is a relationship of sorts between pieces of data. For example, the correlation between how much coffee you drink and how much milk you need to buy. However, correlation does NOT equal causation: two pieces of data trending in the same direction are not necessarily related.

Question 22

Define big-picture thinking from a data analytics perspective

Answer 22

Big-picture thinking is the ability to have a birds eye view of the problem at hand. Big-picture thinking helps you see possibilities and opportunities that you may not see if you were only focusing on an individual piece of the puzzle.

Question 23

Define detail-oriented thinking from a data analytics perspective

Answer 23

Detail-oriented thinking involves focusing on the specifics, the pieces of a puzzle, to make progress.

Question 24

Define ‘root cause’ and explain the five ‘why’s’

Answer 24

The root cause is the reason why a problem occurs. Using the five ‘why’s’ can help you discover the root cause of a problem because each ‘why’ gets you closer to the truth of the problem.

Question 25

Define gap analysis

Answer 25

A method for examining and evaluating how a process currently works in order to get where you want to be in the future. Gap analysis helps you undestand the flaws in a current process and how they can be fixed.

Question 26

What is data-driven decision-making?

Answer 26

Using facts to guide business strategy

Question 27

What is the data ecosystem?

Answer 27

The various elements that interact with one another in order to produce, manage, store, organise, analyse and share data.