09-11-2024 9:00 am - 09-11-2024 6:00 pm
Are you a business analyst looking to analyze data and create insightful reports?
Are you a data analyst wanting to visualize your findings effectively?
Are you a manager or team leader who needs to make data-driven decisions based on reports and dashboards?
Are you someone who is new to Power BI and eager to learn data visualization and reporting basics?
In this program “Become a Power BI Data Analyst In A Day“, you will learn the step-by-step procedure of generating valuable insights in your data by using Power BI desktop and Power BI service.
Why should you attend?
We have more data than we can use. Data is generated by people, processes, tools, operations and more. With this data exploding every day, using business intelligence tools has now become a mandate to analyze trends and make predictions. Among the intelligence tools, Microsoft Power BI is the widely used product and has been positioned as the leader in the 2024 Gartner Magic Quadrant for Analytics and Business Intelligence Platforms.
What are the prerequisites to attend this program?
Hardware and Software prerequisites
– A stable, high-speed internet connection.
– A Windows laptop with Power BI Desktop installed (download PBIDesktopSetup_x64.exe from [this link] and install Power BI Desktop).
– An external mouse for ease of use.
Skill prerequisites
– Familiarity with basic Excel features such as sheets, tables, and formulas. (Quick read here)
– Understanding of database concepts, including tables, columns, normalization, and joins. (Quick read: here)
After the program, you will be able to …
1. Prepare the Data: Ensure data accuracy and reliability for informed decision-making.
1.1. Identify and connect to a data source: Connect to relevant data sources for comprehensive analysis.
1.2. Choose between Import, Direct Query, and Dual mode: Optimize data retrieval methods based on performance needs.
1.3. Evaluate data including statistics and properties: Gain insights into data quality and structure.
1.4. Select appropriate column data types: Ensure proper data handling and analysis.
1.5. Create and transform columns: Enhance data usability for analysis and reporting.
1.6. Configure data loading for queries: Improve query performance and data refresh efficiency.
2. Model the Data: Optimize data relationships for efficient analysis and reporting.
2.1. Design a star schema: Facilitate faster querying and data retrieval.
2.2. Identify and create appropriate keys for relationships: Establish clear connections for accurate data analysis.
2.3. Configure table and column properties: Control data visibility and behavior in reports.
2.4. Define a relationship’s cardinality and cross-filter direction: Ensure correct data context and interactions in analysis.
2.5. Use DAX functions – RELATED, CALCULATE, SUMX – to create calculated columns and measures: Enable advanced calculations for deeper insights.
3. Visualize the Data: Communicate insights effectively through intuitive and interactive visuals.
3.1. Design report layout for different audiences: Tailor reports to meet specific stakeholder needs.
3.2. Insert visuals – bar, line chart, treemap, card, matrix, and slicers: Enhance data presentation and understanding through visuals.
3.3. Insert AI visuals – Q&A, Key Influencer, Decomposition tree: Leverage AI to uncover insights and trends automatically.
3.4. Apply filters at report, page, and visual level: Focus on specific data points for targeted analysis.
3.5. Create hierarchies: Enable drill-down capabilities for detailed insights.
4. Deploy and Share: Collaborate and distribute insights across teams for enhanced decision-making.
4.1. Publish .pbix to workspace: Make reports accessible to relevant stakeholders.
4.2. Share semantic model: Promote consistent use of data across reports.
4.3. Build new content from semantic model: Facilitate the creation of new insights from existing data.
4.4. Create dashboards to present consolidated key metrics at a glance: Provide a quick overview of performance indicators.
4.5. Share reports and dashboards directly and through apps: Enhance collaboration and data-driven decision-making.