2.2.2.Follow thje evidence
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Dashboards are powerful visual tools that help you tell your data story. A dashboard organizes information from multiple datasets into one central location, offering huge time-savings. Data analysts use dashboards to track, analyze, and visualize data in order to answer questions and solve problems. For a basic idea of what dashboards look like, refer to this article: 6 real-world examples of business intelligence dashboards. Tableau is one tool that is used to create dashboards and is covered later in the program.
The following table summarizes the benefits of using a dashboard for both data analysts and their stakeholders.
| Benefits | For Data Analysis | For Stakeholders |
|---|---|---|
| Centralization | Sharing a single source of data with all stakeholders | Working with a comprehensive view of data, initiatives, objectives, projects, processes, and more |
| Visualization | Showing and updating live, incoming data in real time* | Spotting changing trends and patterns more quickly |
| Insightfulness | Pulling relevant information from different datasets | Understanding the story behind the numbers to keep track of goals and make data-driven decisions |
| Customization | Creating custom views dedicated to a specific person, project, or presentation of the data | Drilling down to more specific areas of specialized interest or concern |
* It is important to remember that changed data is pulled into dashboards automatically only if the data structure is the same. If the data structure changes, you have to update the dashboard design before the data can update live.
Here is a process you can follow to create a dashboard:
1. Identify the stakeholders who need to see the data and how they will use it
To get started with this, you need to ask effective questions. Check out this Requirements Gathering Worksheet to explore a wide range of good questions you can use to identify relevant stakeholders and their data needs. This is a great resource to help guide you through this process again and again.
2. Design the dashboard (what should be displayed)
Use these tips to help make your dashboard design clear, easy to follow, and simple:
- Use a clear header to label the information
- Add short text descriptions to each visualization
- Show the most important information at the top
**3. Create mock-ups if desired **
This is optional, but a lot of data analysts like to sketch out their dashboards before creating them.
4. Select the visualizations you will use on the dashboard
You have a lot of options here and it all depends on what data story you are telling. If you need to show a change of values over time, line charts or bar graphs might be the best choice. If your goal is to show how each part contributes to the whole amount being reported, a pie or donut chart is probably a better choice.
To learn more about choosing the right visualizations, check out Tableau’s galleries:
- For more samples of area charts, column charts, and other visualizations, visit Tableau’s Viz Gallery. This gallery is full of great examples that were created using real data; explore this resource on your own to get some inspiration.
- Explore Tableau’s Viz of the Day to see visualizations curated by the community. These are visualizations created by Tableau users and are a great way to learn more about how other data analysts are using data visualization tools.
5. Create filters as needed
Filters show certain data while hiding the rest of the data in a dashboard. This can be a big help to identify patterns while keeping the original data intact. It is common for data analysts to use and share the same dashboard, but manage their part of it with a filter. To dig deeper into filters and find an example of filters in action, you can visit Tableau’s page on Filter Actions. This is a useful resource to save and come back to when you start practicing using filters in Tableau on your own.
Just like how the dashboard on an airplane shows the pilot their flight path, your dashboard does the same for your stakeholders. It helps them navigate the path of the project inside the data. If you add clear markers and highlight important points on your dashboard, users will understand where your data story is headed. Then, you can work together to make sure the business gets where it needs to go.
Consider the different types of dashboards:
- How are the different types of dashboards similar to each other?
- In what ways do they differ?
Write 2-3 sentences (40-60 words) in response to each of these questions. Type your response in the text box below.
Explain:
Great work reinforcing your learning with a thoughtful self-reflection! A few commonalities in these examples include:
- Dashboards are visualizations: Visualizing data can be enormously useful for understanding and demonstrating what the data really means.
- Dashboards identify metrics: Relevant metrics may help analysts assess company performance.
Some differences include the timeframe described in each dashboard. The operational dashboard has a timeframe of days and weeks, while the strategic dashboard displays the entire year. The analytic dashboard skips a specific timeframe. Instead, it identifies and tracks the various KPIs that may be used to assess strategic and operational goals.
Now that you have considered the different types of dashboards, think about the impact that dashboards can have on a company:
- What is an example of a data source a company might use with a dashboard?
- How would a company benefit from a dashboard that uses this data?
- What industries or businesses might benefit from using dashboards more than others?
Now, write 2-3 sentences (40-60 words) in response to each of these questions. Type your response in the text box below.
Explain: Thank you for your response! Dashboards can help companies perform many helpful tasks, such as:
- Track historical and current performance.
- Establish both long-term and/or short-term goals.
- Define key performance indicators or metrics.
- Identify potential issues or points of inefficiency.
While almost every company can benefit in some way from using a dashboard, larger companies and companies with a wider range of products or services will likely benefit more. Companies operating in volatile, or swiftly changing markets like marketing, sales, and tech also tend to more quickly gain insights and make data-informed decisions.
Finally, think about the person you had your data conversation with in the last activity. Based on the notes you took during that conversation:
- Which types of dashboards would you recommend for your conversation partner’s data needs?
- How would the dashboards you recommend help them better accomplish their goals?
Then, write 2-3 sentences (40-60 words) in response to each of these questions. Type your response in the text box below.
Explain:
Great work reinforcing your learning with a thoughtful self-reflection! In this response, you should have applied what you have learned about dashboards so far to the conversation you had in the previous self-reflection activity.
Dashboards can provide convenient access to information and analytics and are easy to use in collaboration. Moreover, they may be tailored to the specific needs of the businesses, like tracking performance towards a milestone.
Using a previous example of the ice cream store, the store owner might use an operational dashboard to track their day-to-day sales. Meanwhile, they might use a strategic dashboard to decide whether they have enough capacity to expand their business.
Fill in the blank: Pivot tables in data processing tools are used to _____ data.
A. populate
B. validate
C. summarize
D. clean
Pivot tables in data processing tools are used to summarize data.
In data analytics, how are dashboards different from reports?
A. Dashboards are used to share updates with stakeholders only periodically. Reports give stakeholders continuous access to data.
B. Dashboards contain static data. Reports contain data that is constantly changing.
C. Dashboards monitor live, incoming data from multiple datasets and organize the information into one central location. Reports are static collections of data.
D. Dashboards provide a high-level presentation of historical data. Reports provide a more detailed presentation of live, interactive data.
The correct answer is C. Dashboards monitor live, incoming data from multiple datasets and organize the information into one central location. Reports are static collections of data. Explain: Dashboards monitor live, incoming data from multiple datasets and organize the information into one central location. Reports are static collections of data.
Describe the difference between data and metrics.
A. Data is quantifiable and used for measurement. Metrics are unorganized collections of facts.
B. Data is quantifiable. Metrics are unquantifiable.
C. Data is a collection of facts. Metrics are quantifiable data types used for measurement.
D. Data can be used for measurement. Metrics cannot be used for measurement.
The correct answer is C. Data is a collection of facts. Metrics are quantifiable data types used for measurement. Explain: Data is a collection of facts. Metrics are quantifiable data types used for measurement.
Return on Investment (ROI) uses which of the following metrics in its definition?
A. Sales and margin
B. Inventory and units
C. Profit and investment
D. Supply and demand
The correct answer is C. Profit and investment. Explain: Return on Investment (ROI) = Profit/Investment.