Course Goals

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# Course Goals

Justin Post

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# Welcome to Big Data Analysis!

What is Big Data?

.left45[
- 5 V's of Big Data
    + Volume
    + Variety
    + Velocity
    + Veracity (Variability)
    + Value
]

.right55[
<img src="data:image/png;base64,#img/big-data-characteristics.png" width="500px" style="display: block; margin: auto;" />
]

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# Course Plan

- Course split into four topics

1. Programming in `python`

2. Big Data Management

3. Modeling Big Data (with `Spark` via `pyspark`)

4. Streaming Data

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# What is Python?

- A very high-level language

- General purpose

- Interpreted language

- Many modules available to form the basis of your program

- Spacing used to write blocks of code

```python
def square(arg1):
    return arg1**2

square(arg1 = 10)
```

```
## 100
```

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# Programming in Python (Prep for Dealing with Big Data)

- `JupyterLab` as our IDE (interactive development environment)
- Basic Use of Python
- Markdown capabilities of `JupyterLab`
- Python Modules

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# Programming in Python (Prep for Dealing with Big Data)

- `JupyterLab` as our IDE (interactive development environment)
- Basic Use of Python
- Markdown capabilities of `JupyterLab`
- Python Modules

<br>

- Basic data types & Writing Functions
- Control flow (if/then/else, Looping)
- Summarizing Data Ideas

---

# Programming in Python (Prep for Dealing with Big Data)

- `JupyterLab` as our IDE (interactive development environment)
- Basic Use of Python
- Markdown capabilities of `JupyterLab`
- Python Modules

<br>

- Basic data types & Writing Functions
- Control flow (if/then/else, Looping)
- Summarizing Data Ideas

<br>

- Compound data types (including `Numpy` arrays, `pandas` data frames)
- Summarizing data
- Common models and model evaluation

---

# What Environment Will We Program In?

[JupyterLab](https://jupyterlab.readthedocs.io/en/stable/getting_started/overview.html)

+ Focused on interactive, exploratory computing
+ Start with Google Colab and move to JupyterLab on a JupyterHub to run spark

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# JupyterLab

- **Notebooks**

+ Work through *cells*
    
    + Cells can contain formatted text (via markdown), python code, or raw text (for JupyterLab)
    
    + Text cells can have math type, images, widgets, and more
    
    + Code cells allow you to submit code and output will be placed below the cell

---

# Recap

.left45[
- 5 V's of Big Data
    + Volume
    + Variety
    + Velocity
    + Veracity (Variability)
    + Value
]

.right45[
- Course split into four topics

1. Programming in `python` (using JupyterLab)

2. Big Data Management

3. Modeling Big Data

4. Streaming Data
]