Week 1 - Introduction

Question 1

Data analysis

Answer 1

• The collecion, transformation, and organisation of data
• In order to draw conclusions
• Make predictions
• drive informed decision making.

Question 2

Data

Answer 2

• We use and create enormous amounts of data all the time.
• When we shop, use the internet, ect.
• It is the worlds most valuable resourse.

Question 3

Data on Data

Answer 3

• Demand for business analytics skills will probably be higher than the demand for any other career (10.9% vs. 5.2%) (Source: Bureau of Labor Statistics)

Question 4

What course will teach

Answer 4

• How to ask the right questions and understand objectives.
• How to effectively clean and organize large amounts of data to make it ready for high-quality analysis.
• Hands-on experience using all kinds of tools and techniques that will help you recognize patterns and uncover relationships between data points.
• Help you communicate the results of your analysis, you will learn how to design visuals and dashboards.

Question 5

Gap Analysis

Answer 5

• 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. Improving accessibility, increasing efficiency, and reducing carbon emissions are examples of improvements that gap analysis can help accomplish.

Question 6

Data Science vs Data Analysis vs Data Analytics

Answer 6

• Data Science is defined as creating new ways of modelling and understanding the unknown by using raw data. They create new question using data.
• Data Analysts is the collection, organisation and transformation of data to draw new conclusions. Using existing data to derive insights
• Data Analytics - is the science of data. It’s a very broad concept that encompasses everything from the job of managing and using data to the tools and methods that data workers use each and every day.

Question 7

Data Analysis Life Cycle

Answer 7

• Ask - ask the important questions. what is my objective
• Prepare - data generation, collection, storage and management
• Process - data cleaning and integrity
• Analyse - data exploration, visualisation and analysis
• Share - communicating and interpreting my results
• Act - putting insights to work and solving problems

Question 8

Data ecosystem

Answer 8

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