onnecting your objective with your data through insights is essential to good data storytelling. In this part of the course, you’ll learn about data-driven stories and their attributes. You’ll also gain an understanding of how to use Tableau to create dashboards and dashboard filters.

• Explain data-driven stories, including reference to their importance and their attributes
• Demonstrate an understanding of how to use Tableau to create dashboards and dashboard filters
• Explain how data stories can be used in different forms of on-the-job communication

Use data to develop stories

Data storytelling

Communicating the meaning of a dataset with visuals and a narrative that are customized for each particular audience

1. Engage your audience
   • Engagement: Capturing and holding someone's interest and attention
     • What role does this audience play?
     • What is their stake in the project?
     • What do they hope to get from the data insights I deliver?
   • A big part of being a data analyst is knowing how to eliminate the less important details. One way to do this is with something called spotlighting.
     • Spotlighting is scanning through the data to quickly identify the most important insights.
2. Create compelling visuals
   • You want to show the story of your data, not just tell it. Visuals should take your audience on a journey of how the data changed over time or highlight the meaning behind the numbers.
   • Use Dashboard: A tool that organizes information from multiple datasets into one central location for tracking, analysis, and simple visualization through tables, charts and graphs
   • A dashboard keeps things neat and tidy and easy to understand.
3. Tell the story in an interesting narrative

Effective data stories

Live versus static

Identifying whether data is live or static depends on certain factors:

• How old is the data?
• How long until the insights are stale or no longer valid to make decisions?
• Does this data or analysis need updating on a regular basis to remain valuable?

Static data involves providing screenshots or snapshots in presentations or building dashboards using snapshots of data. There are pros and cons to static data.

PROS

• Can tightly control a point-in-time narrative of the data and insight
• Allows for complex analysis to be explained in-depth to a larger audience

CONS

• Insight immediately begins to lose value and continues to do so the longer the data remains in a static state
• Snapshots can't keep up with the pace of data change

Live data means that you can build dashboards, reports, and views connected to automatically updated data.

PROS

• Dashboards can be built to be more dynamic and scalable
• Gives the most up-to-date data to the people who need it at the time when they need it
• Allows for up-to-date curated views into data with the ability to build a scalable “single source of truth” for various use cases
• Allows for immediate action to be taken on data that changes frequently
• Alleviates time/resources spent on processes for every analysis

CONS

• Can take engineering resources to keep pipelines live and scalable, which may be outside the scope of some companies' data resource allocation
• Without the ability to interpret data, you can lose control of the narrative, which can cause data chaos (i.e. teams coming to conflicting conclusions based on the same data)
• Can potentially cause a lack of trust if the data isn’t handled properly

Dashboard in Tableau