Data Analytics

Question 1

Six-step data analysis process.

Answer 1

(1) Ask, (2) Prepare, (3) Process, (4) Analyze, (5) Share, (6) Act

Question 2

The Ask step of the data analysis process.

Answer 2

Business challenge, objective, or question. Define the problem. Focus on the actual problem and avoid any distractions. Collaborate with stakeholders. Take a step back and see the whole situation in context.

Question 3

The Prepare step of the data analysis process.

Answer 3

Data generation, collection, storage, and data management.

Question 4

The Process step of the data analysis process.

Answer 4

Data cleaning and data integrity

Question 5

The Analyze step of the data analysis process.

Answer 5

Data exploration, visualization, and analysis. Find patterns, relationships, and trends.

Question 6

The Share step of the data analysis process.

Answer 6

Communicating and interpreting results

Question 7

The Act step of the data analysis process.

Answer 7

Putting insights to work to solve the problem

Question 8

EMC’s Data Analysis Process: Six-steps

Answer 8

(1) Discovery, (2) Pre-processing data, (3) Model planning, (4) Model Building, (5) Communicate results, (6) Operationalize

Question 9

SAS’s Interactive Process: Seven-steps

Answer 9

(1) Ask, (2) Prepare, (3) Explore, (4) Model, (5) Implement, (6) Act, (7) Evaluate

Question 10

Project-based Data Analytics Process: Five-steps

Answer 10

(1) Identifying the Problem, (2) Design data requirements, (3) Pre-processing data, (4) Performing data analysis, (5) Visualizing data

Question 11

Big Data Analytics Process: Nine-steps

Answer 11

(1) Business case evaluation, (2) Data identification, (3) Data acquisition and filtering, (4) Data extraction, (5) Data validation and cleaning, (6) Data aggregation and representation, (7) Data analysis, (8) Data visualization, (9) Utilization of analysis results.

Question 12

Good questions to ask

Answer 12

What is the root cause of the problem?
How do I define success for this project?
What kind of results are needed?
Who will be informed?
Am I answering the question being asked?
How quickly does a decision need to be made?

Question 13

Data analysis

Answer 13

The collection, transformation, and organization of data in order to draw conclusions, make predictions, and drive informed decision-making

Question 14

The 5 key aspects to analytical thinking

Answer 14

Visualization, Strategy, Problem-Orientation, Correlation, and Big-picture and detail-oriented thinking.

Question 15

Gap analysis

Answer 15

Lets you examine and evaluate how a process works currently in order to get where you want to be in the future.

Question 16

What is the life cycle of data?

Answer 16

Plan, capture, manage, analyze, archive and destroy.

Question 17

Plan stage of data life cycle

Answer 17

Decide what kind of data is needed, how it will be managed, and who will be responsible for it.

Question 18

Capture stage of data life cycle

Answer 18

Collect or bring in data from a variety of different sources.

Question 19

Manage stage of data life cycle

Answer 19

Care for and maintain the data. This includes determining how and where it is stored and the tools used to do so.

Question 20

Analyze stage of data life cycle

Answer 20

Use the data to solve problems, make decisions, and support business goals.

Question 21

Archive stage of data life cycle

Answer 21

Keep relevant data stored for long-term and future reference.

Question 22

Destroy stage of data life cycle

Answer 22

Remove data from storage and delete any shared copies of the data.

Question 23

Common problem types

Answer 23

(1) Making predictions, (2) Categorizing things, (3) Spotting something unusual, (4) Identifying themes (5) Discovering connections, (6) Finding patterns

Question 24

Making predictions

Answer 24

using data to make an informed decision about how things may be in the future

Question 25

Categorizing things

Answer 25

assigning information to different groups or clusters based on common features.

Question 26

Spotting something unusual

Answer 26

identify data that is different from the norm

Question 27

Identifying themes

Answer 27

Grouping categorized information into broader concepts

Question 28

Discovering connections

Answer 28

Finding similar challenges faced by different entities, and combining data and insights to address them

Question 29

Finding patterns

Answer 29

using historical data to understand what happened in the past and is therefore likely to happen again.

Question 30

SMART question

Answer 30

Specific, Measurable, Action-Oriented, Relevant, and Time-bound

Question 31

Specific question

Answer 31

Specific questions are simple, significant and focused on a single topic or a few closely related ideas. Does the question address the problem? Does it have context? Will it uncover a lot of the information you need?

Question 32

Measurable question

Answer 32

Measurable questions can be quantified and assessed.

Question 33

Action-oriented question

Answer 33

Action-oriented questions encourage change. Will the answers provide information that helps you devise some type of plan?

Question 34

Relevant question

Answer 34

Relevant questions matter, are important and have significance to the problem you’re trying to solve

Question 35

Time-bound question

Answer 35

Time-bound questions specify the time to be studied.