Connecting Power BI to SQL Databases.

A step by step tutorial. Power BI is a data visualization tool and a business intelligence platform that turns raw data into interactive dashboards and reports. This tool looks to connecting users to various data sources including SQL databases, lets look at two ; Connecting to a local databases(postgresql) Connecting to a cloud sql database (aiven). Connecting to a cloud sql database (Aiven). Aiven is a cloud platform that provides databases services. It requires a certificate which is SSL for connections. Let's start; Create or Log in to aiven. Click the 'Create services'. Choose the provider and region. Click 'Create service' Get connection details Get the following information and note them down. Host Port Database Username Password Download the CA certificate from Aiven. Install the certificate on windows in the Trusted Root Certification Authorities stores. Use DBeaver to connect to Aiven and import the raw dataset. Verify the data to loaded successfully. How to connect Power BI to the database Open Power BI. Click get data to postgreSQL database. Input the server and database. Set the ssl mode. Connect and load the table. Look for the table that you either want to load or transform. You can also choose to clean the data. Cleaning the data Here we will turn the messy raw data into a cleaned dataset that will be used later for our dashboard. Step by step After connecting power BI to aiven and loading the data, will will use the power BI query to clean it. The issues that the data has includes; Text in number column Missing values Mixed capitalisation Mixed date types format The measures and calculations used The measures include; Total revenue Total Units Sold Total Orders Gross Profit Gross Profit Margin Avg Delivery Days Avg Rating The calculations include Sum Count Divide Average The visuals I include in my dashboard; Slicers Pie chart Bar chart Column chart Donut chart Conclusion Building dashboard is a result of importing raw data, connecting Power Bi, cleaning and transforming the data and then finally designing interactive dashboard. The end product helps management to make good data driven decisions.