If you’re a computer science student looking for opportunities, then you have full-stack development, front-end
development, data scientists, AI engineers, data analysts, information security analysts as career options, right?
But apart from this, you can also aspire to become a Power BI developer too.
Power BI tops the list of popular tools due to its ease and interactive visualization. It offers self-service analytics
capability to let end-users create reports and dashboards. The possible career opportunities of the Power BI that
are high in demand are, Power BI developers, Power BI consultants, and Power BI analysts.
- Module 1: Get Started with Microsoft Data Analytics
- Module 2: Prepare Data in Power BI
- Module 3: Clean, Transform, and Load Data in Power BI
- Module 4: Design a Data Model in Power BI
- Module 5: Create Model Calculations using DAX in Power BI
- Module 6: Optimize Model Performance
- Module 7: Create Reports
- Module 8: Create Dashboards
- Module 9: Create Paginated Reports in Power BI
- Module 10: Create and Manage Workspaces
- Module 11: Row-level security
Power BI usage has been growing quickly, with over 80,000 open jobs on LinkedIn. Most business analysts and data analysts use Power BI regularly. By learning Power BI, you can accelerate your career and become a data professional.
This course is presented by :
Microsoft Partner
- Power BI Report development.
- Building Analysis Services reporting models.
- Developing visual reports, KPI scorecards, and dashboards using Power BI desktop.
- Connecting data sources, importing data, and transforming data for Business intelligence.
- Analytical thinking for translating data into informative reports and visuals.
- Capable of implementing row-level security on data along with an understanding of application security layer models in Power BI.
- Should have an edge over making DAX queries in Power BI desktop.
- Expert in using advanced-level calculations on the data set.
- Responsible for design methodology and project documentaries.
- Should be able to develop tabular and multidimensional models that are compatible with data warehouse standards.
- Very good communication skills must be able to discuss the requirements effectively with the client teams, and with internal teams.
