/analyzing-and-visualizing-data-with-splunk

analyse and visualize the data prepared in a software tool called Splunk

MIT LicenseMIT

Analyzing and visualizing data with splunk

Objective

analyse and visualize the data prepared in a software tool called Splunk

Dataset

Data was collected and structured by the Fraud team. This dataset consists of payments from various customers made in different periods and amounts. The feature columns include:

  1. Step: This feature represents the month from the start of the simulation. The steps represent four months that the simulation ran virtually. 0: May 1: June 2: July 3: August
  2. Customer: Customer ID
  3. Age: Categorised age 0.0: <= 18 1.0: 19 - 25 2.0: 26 - 35 3.0: 36 - 45 4.0: 46 - 55 5.0: 56 - 65
  4. Gender: Gender of the customer F: Female M: Male
  5. PostcodeOrigin: The postcode of origin/source.
  6. Merchant: The merchant's ID.
  7. Category: Category of the purchase.
  8. Amount: Amount of the purchase.
  9. Fraud: Target variable that shows if the transaction is fraudulent - 1 or non-fraudulent - 0.

File Structure

The project directory structure is organized as follows:

  • README.md: This readme file providing an overview of the project.
  • dataset/: Directory containing the dataset files.
  • splunk dashboard/: contains splunk dashboard.

Getting Started

To get started with the analysis, follow these steps:

  1. Clone the Repository: Clone the project repository to your local machine.

    git clone <url>

  2. Install Splunk Enterprise on your computer.

  3. Using the “prepared_data” file in dataset, import this file into Splunk.

  4. Study the file using the “Interesting Fields” section in Splunk. This tells you about the data you’re using.

view the dashboard

dwnload the file in splunk dasboard folder and view