Data analytics

Data Collection = Big Data

2 types of data collection:

• Primary Data

• Secondary Data

Structuring of Data

• Unstructured Data - Images, audious,essays

• Semi-structured Data - Partially organised (not in format)

• Structed Data - Organised in table form

Types of data values

• Quantitative - Numerical ( Called ' Discrete' if whole number

• Qualitative - Categorical : (eg: No of children)

• Binary - 2 categories

• Ordinary - Ordered category

• Date/Time

• Identity

Remark: However, this course is only focusing on structured data

Types of Structured Data

Table (CSV, xls, gsheet)

Labelled & Unlabelled Data

• Labelled Data = Independent (more than one) & dependent column (one_high priority) - You will use SUPERVISED MACHINE LEARNING TECHNIQUE

• Unlabelled = Only independent column -  You will use UNSUPERVISED MACHINE LEARNING TECHNIQUE

**Fun fact! Most images and videos are unlabelled data

4 Types of Data Analytics

1. Descriptive Analytics - What happened? - Output in the form of graph/chart

2. Diagnostics Analytics - Why did it happen? - Insight

3. Prescriptive Analytics - What action should be taken? - Insight

4. Predictive Analytics - What will happen? -  Output in the form of graph/chart

So what's the difference between a Data Analyst and a Data Scientist?

Data Scientists will do all 4 types of DA

Data Analysts only do Descriptive Analytics & Diagnostic Analytics