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Highlights
Databases
Project files of the article featured here: http://db.rstudio.com/best-practices/dashboards/
Using the rhandsontable library to edit data and generating corresponding SQL insert/update queries.
A "Hello-World" Example of how to use basic Bootstrap modals and a SQLite Database to facilitate application logins at the app level, allowing storage of information and settings instead of just ac…
Developed a web application/dashboard by connecting to a sql database.
A shiny module to authenticate your R Shiny Application with a PostgreSQL Database.
Final project of module "databases and datawarehousing" @ ZHAW CAS information engineering.
A demo shiny app demonstrating a backend database hosted on aws
This repository is based in "R Shiny" with a connection to a MySql Database and an option to upload Excel files to bulk inserts.
Store and manage samples in SQL database through shiny application.
Deterministic, documented correction rules on a database
R package for fast bulk imports/exports from/to SQL Server with the bcp command line utility
Functions that generate SQL queries that summarize high-dimensional tables stored in various databases (e.g. Microsoft SQL Servers, Netezza, DB2, Postgres, Oracle, MySQL, etc.).
This RShiny app summarizes large tables stored in database servers
This is the repository for the project of Database
The idea is to use the SQL skills in R by converting data into relational database from text files and then using it to run queries to filter data by SQL
DDL & test data for different databases for ETL data quality checks / data loading tests
Utilizes MS SQL metadata to document any given database.
PRQL is a modern language for transforming data — a simple, powerful, pipelined SQL replacement
Technical documentation for Microsoft SQL Server, tools such as SQL Server Management Studio (SSMS) , SQL Server Data Tools (SSDT) etc.
Query git repositories with SQL. Generate reports, perform status checks, analyze codebases. 🔍 📊
The missing set of useful tools for Postgres DBAs and all engineers
The fastest ⚡️ way to build data pipelines. Develop iteratively, deploy anywhere. ☁️





