10 Tools for SQL Developers π π -
π SQL Server Management Studio (SSMS) - Manage and query SQL Server databases
π phpMyAdmin - Web-based tool for MySQL database management
π DBeaver - Universal database management tool
π Tableau - Data visualization and BI tool
βοΈ SQL Workbench/J - Cross-platform SQL query tool
π pgAdmin - Management tool for PostgreSQL
π Azure Data Studio - Lightweight and extensible data tool
π¦ Toad for SQL - Database development and administration
π Datagrip - JetBrains SQL IDE for various databases
π HeidiSQL - Lightweight MySQL and MSSQL client
#SQLTools #DataAnalysis
π SQL Server Management Studio (SSMS) - Manage and query SQL Server databases
π phpMyAdmin - Web-based tool for MySQL database management
π DBeaver - Universal database management tool
π Tableau - Data visualization and BI tool
βοΈ SQL Workbench/J - Cross-platform SQL query tool
π pgAdmin - Management tool for PostgreSQL
π Azure Data Studio - Lightweight and extensible data tool
π¦ Toad for SQL - Database development and administration
π Datagrip - JetBrains SQL IDE for various databases
π HeidiSQL - Lightweight MySQL and MSSQL client
#SQLTools #DataAnalysis
π1
Don't waste your lot of time when learning data analysis.
Here's how you may start your Data analysis journey
1οΈβ£ - Avoid learning a programming language (e.g., SQL, R, or Python) for as long as possible.
This advice might seem strange coming from a former software engineer, so let me explain.
The vast majority of data analyses conducted each day worldwide are performed in the "solo analyst" scenario.
In this scenario, nobody cares about how the analysis was completed.
Only the results matter.
Also, the analysis methods (e.g., code) are rarely shared in this scenario.
Like for next steps
#dataanalysis
Here's how you may start your Data analysis journey
1οΈβ£ - Avoid learning a programming language (e.g., SQL, R, or Python) for as long as possible.
This advice might seem strange coming from a former software engineer, so let me explain.
The vast majority of data analyses conducted each day worldwide are performed in the "solo analyst" scenario.
In this scenario, nobody cares about how the analysis was completed.
Only the results matter.
Also, the analysis methods (e.g., code) are rarely shared in this scenario.
Like for next steps
#dataanalysis
π7