Understanding Data Storytelling

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Match the following data visualization types with their descriptions:

Scatter plot = Displaying the relationship between two variables Geographic map = Showing data points on a map Line graph = Illustrating trends over time Pie chart = Representing parts of a whole

Match the following steps of storytelling with data with their descriptions:

Identify your story = Begin by determining the main message you want to convey Craft a great story = Utilize various types of data and visualizations to build a compelling narrative Link visualization with narrative = Connect the visualizations with a storyline to explain the 'why' behind the data Connect with the audience = Make data-driven decisions by engaging the audience through storytelling

Match the following characteristics of effective storytelling with their descriptions:

Establishing connections between events = Providing order and coherence to a series of facts or events Skills familiar to movie directors = Requiring abilities beyond technical expertise in computer engineering and science Answering the 'why' question = Linking visualizations with a narrative to provide context and reasoning Supporting a hypothesis = Creating a cohesive narrative using collected data and analytics

Match the following key reasons for data storytelling with their descriptions:

Answering 'why' questions = Providing contextual information and reasoning behind visualized data Connecting visualization and narration = Linking visual representations with a compelling storyline Making data-driven decisions = Engaging the audience through storytelling to influence decision-making Supporting hypotheses = Creating a cohesive narrative using collected data and analytics

Match the following programming languages with their primary usage:

Python = General-purpose programming JavaScript = Client-side scripting for web applications SQL = Database queries CSS = Styling web pages

Match the following storytelling genre with its description:

Magazine Style = A format resembling a magazine layout, often used for presenting data in a visually appealing manner Annotated Chart = A chart or graph that includes additional explanatory text or annotations to provide context and insights Partitioned Poster (Infographic) = A visual representation that uses elements like icons, images, and minimal text to convey complex information in a concise and engaging way Slideshow = A series of visual slides or images presented sequentially to convey a story or message

Match the following steps of storytelling with data with their descriptions:

Collect your data = Identifying the most important data and determining the goal of data collection Be aware of your audience = Understanding the audience's expectations, knowledge level, and preferred level of data detail Transform the data to data visualization = Converting raw data into visual representations such as charts or graphs to answer specific questions Generate your insights / Narration = Explaining the 'why' behind the visualization and concluding with actionable insights for the audience

Match the following points about visual storytelling with their descriptions:

A picture is worth a thousand words = Emphasizing the power of visuals to convey complex information more effectively than lengthy descriptions Visual Storytelling A picture is worth a thousand words = Evaluating whether a visual effectively conveys its point and if the story is clear and understandable Visual as Props in Storytelling = Stating that a data visual should serve as a prop for the storyteller rather than telling the entire story itself Avoid the Analysis Journey = Advising analysts to focus on producing graphs that support the audience's business story rather than emphasizing their own analysis journey

Match the following aspects of audience consideration with their descriptions:

Familiarity with your topic = Assessing the audience's knowledge and interest in the subject matter being presented How do they encounter your visualization = Considering whether the audience will view the visualization on mobile phones, computers, or in print media What do you want them to take away = Determining the key points or insights that you aim for the audience to remember after viewing the visualization What do they know about visualization = Evaluating the audience's level of understanding and familiarity with data visualization concepts

Match the following recommendations about using data visuals with their descriptions:

Create a data visual to reveal the data in a story = Using visuals to present data that guides managers towards making informed decisions on business issues Avoid using too many words to describe data points = Emphasizing the use of visuals to illustrate key points rather than relying solely on textual descriptions Choose graphs that support the business story that matters to the audience = Selecting graphs based on their relevance to the audience's business journey rather than showcasing an analyst's personal analysis process A data visual should not tell the whole story but be a prop to be used by the storyteller = Stressing that visuals should complement storytelling rather than independently conveying all aspects of a narrative

Test your knowledge of data storytelling and learn about creating a narrative using collected data and analytics to support a hypothesis, presenting a cohesive narrative, and using various types of data visualizations.

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