Cracking the Code: A Comprehensive Data Analysis Journey

 The data analysis process

1- Prepare the data

2- Model

3- Analyze

- Descriptive Analysis: Describe what the data looks like in its basic form.

- Exploratory Analysis: Dig deeper to try and find interesting patterns or relationships between different parts of the data.

- Inferential Analysis: Use available data to make guesses or predictons about things outside the data.

- Predictive Analysis: Use statistics to predict what might happen in the future based on what's happened in the past.

4- Visualize

5- Manage

Gathering the right data

1- Identify the Analysis Purpose

for example: Drive product development

2- Type of Data

for example: Market trends data

                               Competitor data

                               Sales Data

3- Scope of Data

For example: Dates: last 5 years

                               Products: Mountain and road bikes

                               Regions: Europe

Processing and Analzing the data 

Define Analysis Purpose

Data collection ; "Raw data" For example: Sales

                                 Customer

                                 Manufacturing

                                                                                                                       Purchasing

                                                                                                         Inventory

                                                                                                         Marketing

Data Processing

Data exploration and analysis

Data reporting

Example issues of raw data

1- Duplicate entries

2- Missing values

3- Different format

4- Multiple sources

We can fix these issues with ETL Process:

Extract

Transform

Load