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Data Storytelling with Power BI

This Power BI training course delves into the art of data storytelling, where participants learn how to use Power BI to craft data-driven narratives that resonate with diverse audiences. Beginning...

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$875 USD
Course Code PBI-130WA
Duration 2 days
Available Formats Classroom

This Power BI training course delves into the art of data storytelling, where participants learn how to use Power BI to craft data-driven narratives that resonate with diverse audiences. Beginning with the basics of data storytelling, attendees progressively build compelling visualizations and reports that summarize historical data, identify reasons behind past events, make informed forecasts about future events, and provide deep insights into data.

Skills Gained

  • Understand effective data storytelling
  • Apply data storytelling best practices
  • Select and create compelling visualizations
  • Communicate complex insights effectively
  • Drive informed decisions from raw data
  • Deliver data insights using dashboards, scorecards/metrics, and apps

Prerequisites

Familiarity with Excel and Power BI is useful but not necessary.

Course Details

Training Materials

All Report Users/Power BI training students receive comprehensive courseware.

Software Requirements

  • A recent version of Windows (Windows 10 or later) with at least 8 GB of RAM
  • Microsoft 365 installed (especially Excel)
  • Power BI Desktop installed
  • Internet connectivity (for connecting to the Power BI service)
  • Related lab files that Accelebrate provides

Course Outline

Understanding Data Storytelling and Data Analytics

  • What is Data Storytelling?
  • The three key elements of data storytelling
  • Identify your objective and target audience
  • Craft a clear narrative flow
  • Define a story arc
  • Understanding the role of Data Analytics in Data Storytelling
  • Distinguishing Between Descriptive, Diagnostic, Predictive, Prescriptive, and Cognitive Analytics
  • Selecting the right data visualization
  • Visualization mistakes to avoid

The End-to-End Process

  • Understanding the End-to-End Process
  • Data Preparation: Transforming Raw Data
  • Data Modeling: Structuring for Analysis
  • Visualization: Crafting Compelling Data Stories
  • Publishing Reports
  • Creating Dashboards and Metrics/Scorecards
  • Packaging as an Application
  • Effective Distribution Strategies
  • Consuming Insights and Making Informed Decisions

Your Story: Summarizing Historical Data to Provide Insights

  • Presenting raw data and statistics
  • Summarizing categorical data and displaying frequencies
  • Tracking trends and changes over time
  • Displaying proportions and percentages
  • Displaying patterns and correlations

Your Story: Identifying the Reasons Behind Past Events and Patterns

  • Identifying relationships and correlations between variables
  • Analyzing data distributions
  • Visualizing data variability and identifying outliers
  • Exploring details and root causes

Your Story: Make Informed Forecasts About Future Events and Trends

  • Utilizing predictive modeling for future trends
  • Predicting outcomes based on historical data
  • Segmenting data and identifying patterns
  • Identifying unusual data points

Your Story: Recommend Specific Actions

  • Implementing scenario analysis and decision support
  • Identifying factors impacting a specific outcome
  • Visualizing paths and outcomes based on decisions
  • Optimization and goal-based analysis

Your Story: Analyzing Data in a Human-like Manner

  • Interact with data using plain language
  • Using built-in AI visuals
  • Overview of Sentiment Analysis and Image Recognition

Creating Engaging Stories with Interactive Elements

  • Understanding conditional formatting options
  • Adding images and hyperlinks to a table
  • Working with databars, sparklines, and indicators
  • Working with sync slicers
  • Working with tooltip popup
  • Implementing bookmarks, buttons, and selections

Delivering Data Insights

  • Publishing Reports
  • Creating Dashboards and Metrics/Scorecards
  • Packaging as an Application
  • Effective Distribution Strategies
  • Consuming Insights and Making Informed Decisions

Data Storytelling Best Practices

  • Context is everything!
  • Data visualization decluttering best practices
  • Using text appropriately
  • Visualization mistakes to avoid

Conclusion