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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: ...

2 Top Tableau Unique Features

Tableau is one of the most popular tools in data analysis. Learning the Tableau gives you so many options in data analysis career.

tableau features
You can download Tableau Software free version here. Get a complete understanding document on how Tableau works here. Read this post for advancing in your Tableau Career.

Unique functionality in Tableau

Tableau Software was founded on the idea that analysis and visualization should not be isolated activities but must be synergistically integrated into a visual analysis process. Visual analysis means specifically:

1). Data Exploration


Visual analysis is designed to support analytical reasoning. The goal of the visual analysis is to answer important questions using data and facts. In order to support analysis, it is not enough to only access and report on the data.

Analysis requires computational support throughout the process. Typical steps in the analysis include such operations as
  • filtering to focus on items of interest
  • sorting to rank and prioritize
  • grouping and aggregating to summarize
  • creating on-the-fly calculations to express numbers in useful ways. A visual analysis application exposes these exploratory operations to ordinary people through easy-to-use interfaces.
Related: Tableau 9 Advanced Training

2). Data Visualization

Visual analysis means presenting information in ways that support visual thinking. Data is displayed using the best practices of information visualization. The right presentation makes it easy to organize and understand the information.

For example, critical information may be quickly found, and features, trends, and outliers may be easily recognized. One powerful way to evaluate any analysis tool is to test its effectiveness in answering specific questions.
At the most fundamental level, does the tool have the analytical power needed to answer the question?
At another level, how long does it take to answer the question? A successful visual analysis application unites data exploration and data visualization in an easy-to-use application that anyone can use.

Daily use Tableau commands

addusers (to group)
creategroup
createproject
createsite
createsiteusers
createusers
delete workbook-name or datasource-name
deletegroup
deleteproject
deletesite
deletesiteusers
deleteusers
editdomain
editsite
export
get url
listdomains
listsites
login
logout
publish
refreshextracts
removeusers
runschedule
set
syncgroup
version

YouTube tutorial for beginners:


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