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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

Analyst and Data Scientist Career Options

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 The following Skillset needed to succeed as Analyst or Data Scientist career. DTD Frame work: Understanding and hands on experience of Data to decisions frame work. SQL Skills: Experience to pull data from multiple sources. Hands on experience of Teradata, Oracle and Hadoop skills also useful Basic Statistics Techniques: Hands-on experience with basic statistical techniques: Profiling, Correlation analysis, Trend analysis, Sizing/Estimation, Segmentation Business Side Experience: Working with all business stake holders. Communication and influencing others. Advanced statistics: Hands-on comfort with advance techniques: Time Series, Predictive Analytics – Regression and Decision Tree, Segmentation (K-means clustering) and Text Analytics (optional) Read more