Necessary cookies are absolutely essential for the website to function properly. Lesson 10: Presenting Insights with Reports Topic D: Perform Advanced Data Analysis and Visualization.Topic B: Create Data Models with Power Pivot.Lesson 9: Modeling and Analyzing Data with Power Pivot Topic B: Analyze Data with the Data Analysis ToolPak.Topic A: Visualize Trendlines and Sparklines with Excel.Lesson 7: Performing Statistical Analysis Lesson 6: Creating Geospatial Visualizations with Excel Topic B: Filter Data Using Slicers and Timelines.Topic A: Visualize Data with PivotCharts.Lesson 5: Presenting Visual Insights with Dashboards in Excel Lesson 4: Analyzing Data with PivotTables Topic D: Create Conditional Visualizations with Lookup Functions.Topic C: Implement Data Validation, Forms, and Controls.Topic A: Analyze Data with Formulas and Named Ranges.Lesson 3: Analyzing Data with Formulas and Functions Topic C: Apply Best Practices in Chart Design.To find out when this course is being offered next, please refer to our Course Schedule. These capabilities enable people who use Excel for data analysis to turn data into thoughtful action. Excel can connect to a wide range of data sources, perform robust data analysis, and create diverse and robust data-backed visualizations to show insights and trends, and create reports. Microsoft Excel is designed for this purpose. Beyond the analysis, data analysts in all job roles must be able to effectively present and communicate their findings in visually compelling ways. Leveraging that data effectively can provide timely insights and a competitive advantage.Īnalyzing data to find issues, insights, and opportunities is now a critical part of many job roles. The era of “big data” has exploded due to the rise of cloud computing, which provides an abundance of computational power and storage, allowing organizations of all sorts to capture and store data. Technology and the data that it both collects and makes accessible is now interwoven with businesses and lives.
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