$\Large{\color{blue}\underline{\mathcal{Data\ Analysis\ with\ Python:}}}$

$\Large{\color{Purple}\underline{\textrm{Learning objectives}}}$

1. Define data and its importance.
2. Define data analytics and its types.
3. Explain why analytics is important in today's business environment.
4. Explain how statistics, analytics and data science are interrelated.
5. Why python?
6. Explain the four different levels of Data:
   • Nominal
   • Ordinal
   • Interval and
   • Ratio

$\large{\color{Purple}1. \underline{\textrm{Define Data and its importance}}}$

• Variable, Measurement and Data
• What is generating so much data?
• How data add value to the business?
• Why data is important?

$\large{\color{Purple}1.1 \underline{\textrm{Variable, Measurement and Data}}}$

• Variables – is a characteristic of any entity being studied that is capable of taking on different values
• Measurements is when a standard process is used to assign numbers to particular attributes or characteristic of a variable
• Data – data are recorded measurements

$\large{\color{Purple}1.2 \underline{\textrm{What is generating so much data?}}}$

• Data can be generated by
  • Humans,
  • Machines or
  • Humans-machines combines
• It can be generated anywhere where any information is generated and stored in structured or unstructured formats

$\large{\color{Purple}1.3 \underline{\textrm{How data add value to the business?}}}$

$\large{\color{Purple}1.4 \underline{\textrm{Why data is important?}}}$

• The data helps in making better decisions
• Data helps in solve problem by finding the reason for underperformance.
• Data helps one to evaluate the performance.
• Data helps one improve processes.
• Data also can help one understand the consumers and the markets.

$\large{\color{Purple}2. \underline{\textrm{Define data analytics and its types}}}$