Duration: 2 days

Overview

In this Power BI training course, attendees learn how to transform raw data into compelling data storytelling narratives that drive informed decisions.

Objectives

  • Grasp the fundamentals of data storytelling and its role in data analytics
  • Apply data storytelling best practices to craft impactful narratives
  • Select and create compelling visualizations that effectively convey insights
  • Communicate complex data insights clearly and persuasively
  • Transform raw data into actionable insights that inform decision-making
  • Deliver data insights using various methods, including dashboards, scorecards/metrics, and apps

Prerequisites

It would be helpful for students to be familiar with Excel and Power BI.

Outline for Data Storytelling with Power BI Training

  • 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