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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

Data analysis report these are example queries to use on final data

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ApplyAnalytics@twitter The role of data analysis will come into picture, once you have cleaned and filter the raw unstructured data. The next stage is called analysis. Your success of data analysis project is based preparing highly informative final report. Tip:  What could you investigate with data To prepare analysis report, you need to ask some intelligent questions. These are example questions you can use. Based on your questions, you  need to prepare SQL queries to get the desired report or dashboard from your final data or cleaned data.  The report or dashboard should be such that it should improve client business. Let us use some case study on world bank data, what are the questions come into mind:  How much (in USD) is spent on healthcare in total in each country?  How much (in USD) is spent per capita in each country?  In which country is the most spent per person?  In which country is the least spent?  What is the average for each