Data Storytelling — Learn free

Self-check

Questions 1–10 of 10

1. What is data storytelling?
Question 1A. The art of translating complex data into a compelling narrative that drives actionB. Writing fictional stories using random numbersC. Storing data in narrative text filesD. Presenting raw tables without commentaryE. A method for encrypting spreadsheets
2. In data storytelling, who are the 'characters' of the story?
Question 2A. The columns of a datasetB. The key stakeholders, such as business leaders, data teams, regulators and end-usersC. The visualisation toolsD. The fictional personas invented for a presentationE. The database administrators only
3. In the banking example of data storytelling, which of the following is NOT listed among the key stakeholders for improving customer satisfaction?
Question 3A. Bank ManagersB. CustomersC. Software vendorsD. Loan OfficersE. Regulators
4. What provides the 'context' in data storytelling?
Question 4A. The colour scheme of the chartsB. The number of slides in the presentationC. The list of database tablesD. Linking data to the organisation's strategic goals and key performance indicators (KPIs)E. The names of the data engineers
5. In the banking example, which KPIs are tracked by a bank that wants to reduce customer complaints?
Question 5A. Number of branches, number of ATMs and staff countB. Share price, dividend yield and market capitalisationC. Server uptime, database size and query latencyD. Marketing spend, advertising reach and brand awarenessE. Average wait time, loan approval speed and customer retention rate
6. In data storytelling, what plays the role of the story's conflict?
Question 6A. The Cost of Inaction (COI): the risks of not acting on data insightsB. Disagreements between data engineers and analystsC. The choice between two visualisation toolsD. The budget negotiation for the projectE. The competition between departments for data access
7. In the banking example, which of the following is a risk of inaction when transaction data is collected but not analysed properly?
Question 7A. Too many customers opening accountsB. Increased fraud cases because suspicious transactions are not detected earlyC. Excessive compliance with regulationsD. Loan approvals becoming too fastE. Shorter customer wait times
8. What does defining a strategic resolution path involve in data storytelling?
Question 8A. Choosing which stakeholders to excludeB. Deleting data that contradicts the storyC. Establishing a clear vision, milestones and execution plan to drive meaningful outcomesD. Writing a fictional happy endingE. Selecting the loudest stakeholder's preferred option
9. In the banking example of reducing loan approval time, what is the first step of the resolution path?
Question 9A. Automate verification processes with AIB. Monitor and improveC. Gather customer feedbackD. Identify the delay points by analysing past loan applicationsE. Hire more loan officers
10. What are the four elements that together allow data storytelling to create real-world impact?
Question 10A. Collecting, cleaning, storing and archiving dataB. Charts, tables, slides and reportsC. Budget, staff, tools and timelinesD. Extraction, transformation, loading and servingE. Engaging stakeholders, understanding business context, assessing risks and defining a resolution path