> For the complete documentation index, see [llms.txt](https://docs.launchboard.app/industry-connect-2024/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.launchboard.app/industry-connect-2024/founding-cohort/projects/data-analytics-project.md).

# Data Analytics Project

Demonstrating data-driven decision-making

{% embed url="<https://www.loom.com/share/f39cf72c01674e3dac23751c1a67b60c?sid=10ff5d04-0b1d-4110-ba02-4dac6ae080dc>" %}

It's time to demonstrate your new knowledge by applying it to a real-world scenario. Specifically, you want to demonstrate a ***data-driven decision-making*** process by applying spreadsheet and SQL skills. This is an individual project, but you can help each other out.

## Learning Objectives

* Demonstrate skills in filtering and sorting data using SQL
* Demonstrate skills in creating well-formatted spreadsheet charts &#x20;
* Compose a short report applying a data-driven decision-making process

## Resources

* SQL Lab for Ready-to-Go Data: <https://sql.launchboard.app/>
* Report Template: <https://docs.google.com/document/d/18qyWfMSiyTQIM8daPGdSCb-1sYZv8dk6HTitKrWW0Fk/edit?usp=sharing>

***

## Instructions

### <mark style="color:red;">1. Research the Problem Domain</mark>

* **Determine a domain you are interested investigating**. \
  (e.g. movies, sports stats, health data, financial data, etc.)
* **Define a scenario for your project that includes decisions** — or questions that need answered.\
  For example, an upstart movie production firm wants to investigate what genre of movies they should focus on, and they may use recent data on movies, including budget, sales, genre, location, etc. Formulate at least two well-defined questions.
* **Identify potential data sources**\
  You can use thoughtful internet searches or use platforms like Kaggle to look for data. You may also find organizations that post data on specific topics.&#x20;

### <mark style="color:red;">2. Process the Data</mark>

* **Filter, sort, and clean the data as needed with SQL and spreadsheets**\
  The process you use will be unique to your project, but you will need to do drill down to the data you want to look at related to your questions.

### <mark style="color:red;">3. Chart the Data and Tell the Story</mark>

* **Create at least two charts that visually help answer your project questions**.\
  Ensure that you format and label them well. They should be easy to view and provide a concise representation of the data.
* **Compose a short report that explains the purpose and analysis of your project.**\
  Follow this basic outline. One to two pages should be sufficient.
  * Title
  * Introduction to the project background
  * Data sources
  * Charts with an explanation of each
  * Conclusions

### Example Layout

<figure><img src="https://1625728016-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2Fk2eSlWeIIlewSK7TTGHl%2Fuploads%2FahofzKsxUK72btkoQxCp%2Fimage.png?alt=media&amp;token=09ad0891-d211-4576-a59a-2b07b003c79d" alt=""><figcaption></figcaption></figure>


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