How do tools like Python, SQL, Power BI, and Tableau complement each other in a data analytics workflow?

In real-world projects I’ve handled and discussions at H2kinfosys, tools like Python, SQL, Power BI, and Tableau complement each other by covering different stages of the analytics workflow. SQL is primarily used to extract and query structured data from databases. Python helps clean, transform, and analyse large datasets, and can perform statistical modelling or automation. Once insights are generated, Power BI and Tableau convert processed data into interactive dashboards for business stakeholders. This layered approach ensures accuracy, efficiency, and clarity in decision-making. Many professionals gain integrated exposure to these tools through a Data analytics bootcamp that simulates end-to-end business scenarios.