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How to Build CI/CD Pipeline: GitHub to AWS

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 Creating a CI/CD pipeline to deploy a project from GitHub to AWS can be done using various AWS services like AWS CodePipeline, AWS CodeBuild, and optionally AWS CodeDeploy or Amazon ECS for application deployment. Below is a high-level guide on how to set up a basic GitHub to AWS pipeline: Prerequisites AWS Account : Ensure access to the AWS account with the necessary permissions. GitHub Repository : Have your application code hosted on GitHub. IAM Roles : Create necessary IAM roles with permissions to interact with AWS services (e.g., CodePipeline, CodeBuild, S3, ECS, etc.). AWS CLI : Install and configure the AWS CLI for easier management of services. Step 1: Create an S3 Bucket for Artifacts AWS CodePipeline requires an S3 bucket to store artifacts (builds, deployments, etc.). Go to the S3 service in the AWS Management Console. Create a new bucket, ensuring it has a unique name. Note the bucket name for later use. Step 2: Set Up AWS CodeBuild CodeBuild will handle the build proces
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5 SQL Queries That Popularly Used in Data Analysis

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 Here are five popular SQL queries frequently used in data analysis.


5 SQL Queries Popularly Used in Data Analytics




1. SELECT with Aggregations

Summarize data by calculating aggregates like counts, sums, averages, etc.

SELECT department, COUNT(*) as employee_count, AVG(salary) as average_salary
FROM employees
GROUP BY department;


2. JOIN Operations

 Combine data from multiple tables based on a related column.

SELECT e.employee_id, e.name, d.department_name
FROM employees e
JOIN departments d ON e.department_id = d.department_id;

3. WHERE Clause for Filtering

Filter records based on specified conditions.

SELECT *
FROM sales
WHERE sale_date BETWEEN '2024-01-01' AND '2024-12-31'
  AND amount > 1000;

4. ORDER BY Clause for Sorting

Sort results in ascending or descending order based on one or more columns.

SELECT product_name, price
FROM products
ORDER BY price DESC;

5. GROUP BY with HAVING Clause

Group records and apply conditions to the aggregated results.

SELECT department, SUM(salary) as total_salaries
FROM employees
GROUP BY department
HAVING SUM(salary) > 50000;

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