Data Analytics Concepts

Question 1

What is data analytics?

Answer 1

The process of examining data sets to draw conclusions about the information they contain, often using specialized systems and software.

Question 2

What are the four main types of data analyitics?

Answer 2

Descriptive - What happened?
Diagnostic - Why did it happen?
Predictive - What might happen?
Prescriptive - What should we do about it?

Question 3

What is data literacy?

Answer 3

The ability to read, understand, create, and communicate data as information. It helps businesses make informed, data-driven decisions.

Question 4

Why is data literacy critical for business today?

Answer 4

Because decisions based on real behavior and trends are more effective than gut instincts or outdated info. It gives companies a competitive edge.

Question 5

What is data science?

Answer 5

A field that combines statistics, computer science, and domain expertise to extract meaningful insights from structured and unstructured data.

Question 6

What is the difference between data science and data analytics?

Answer 6

Data analytics focuses on interpreting existing data to identify trends.

Data Science builds models and algorithms to predict or automate future decisions based on data.

Question 7

What are the key steps in a data science project?

Answer 7

1. Define the problem
2. Collect Data
3. Clean and preprocess data
4. Explore Data (EDA)
5. Build models
6. Evaluate models
7. Communicate results

Question 8

What is exploratory data analysis (EDA)?

Answer 8

A process of analyzing datasets to summarize their main characteristics, often using visualizations, before formal modeling.

Question 9

What is the difference between supervised and unsupervised learning?

Answer 9

Supervised Learning: Uses labeled data

Unsupervised Learning: Finds hidden patterns in unlabeled data.

Question 10

What is overfitting in machine learning?

Answer 10

When a model learns the training data too well, including its noise, and performs poorly on new, unseen data.

Question 11

What is a feature in a dataset?

Answer 11

An individual measurable property or characteristic of the data

Question 12

What is the role of statistics in data science?

Answer 12

Statistics helps interpret data, test hypotheses, and validate model performance

Question 13

What does “Correlation does not imply causation” mean?

Answer 13

Just because two variables move together doesn’t mean one causes the other. There may be a third factor or coincidence involved.