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Step-by-Step Guide to Creating an AWS RDS Database Instance

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 Amazon Relational Database Service (AWS RDS) makes it easy to set up, operate, and scale a relational database in the cloud. Instead of managing servers, patching OS, and handling backups manually, AWS RDS takes care of the heavy lifting so you can focus on building applications and data pipelines. In this blog, we’ll walk through how to create an AWS RDS instance , key configuration choices, and best practices you should follow in real-world projects. What is AWS RDS? AWS RDS is a managed database service that supports popular relational engines such as: Amazon Aurora (MySQL / PostgreSQL compatible) MySQL PostgreSQL MariaDB Oracle SQL Server With RDS, AWS manages: Database provisioning Automated backups Software patching High availability (Multi-AZ) Monitoring and scaling Prerequisites Before creating an RDS instance, make sure you have: An active AWS account Proper IAM permissions (RDS, EC2, VPC) A basic understanding of: ...
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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)

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