data visualization competition 2021

It's all about presenting the data clearly and highlighting the key points. You need to make it easy for people to understand the story the data is telling.

You need to start by having a clear message and choosing the right data to support it. Then, use simple and intuitive visual elements to present the data clearly.

Data visualization tells a story by converting numbers and information into visuals. It focuses attention on key points, highlights comparisons, and enables us to draw conclusions quickly. Like a pie chart can show the proportion of different parts in a whole, creating a visual story of the distribution.

One of the best data visualization stories is Hans Rosling's work on visualizing global health and economic data over time. His animated graphs showed how countries' life expectancies and incomes had changed in an engaging and intuitive way. It made complex data accessible to a wide audience.

First, clearly define your message. Know what you want to convey through the data. For example, if you want to show the growth of a company's sales over the years, that's your core message. Then, choose the right data set that supports this message. After that, pick an appropriate visualization type like a line graph for trends or a pie chart for proportions.

You can start by choosing the right data that's relevant and interesting. Then, use clear and simple charts or graphs to make the data easy to understand. Add some context and explanations to help the audience connect the dots.

A major benefit is enhanced discovery. When it's more than a story, it encourages users to find things in the data that were unexpected. Consider a visualization of social media data. Users might stumble upon new correlations between user demographics and content sharing that were not part of an initial story, leading to new research directions or marketing strategies.

Data visualization can be more than telling a story by providing in - depth analysis. It allows viewers to explore data on their own, discover patterns and trends that might not be part of a pre - defined narrative. For example, in a scatter plot, users can look for outliers or clusters that could lead to new insights not included in a simple story - based presentation.

Well, data visualization in finance simplifies data. It helps communicate financial information quickly and accurately. Also, it can highlight important insights and comparisons that make the story more compelling and persuasive to stakeholders.

The Qinghuangdao Big Data Visualization Training Course usually includes the following contents: Basic knowledge of data visualization: introduce the basic concepts, tools, and techniques of data visualization, including chart making, data exploration, data visualization style, etc. 2. Use of data visualization tools: Explain how to use common data visualization tools such as Tableau, Power Bi, MatplotLib, etc. to visualize data. 3. Data visualization strategy and design: introduce the design principles, strategies and techniques of data visualization, including data pre-processing, data cleaning, data transformation, data exploration, data visualization architecture, etc. 4. Teaching with practical cases: Through practical cases, the students will explain how to use the knowledge they have learned to visualize data, including the selection of data sources, data cleaning, data conversion, chart making, interaction design, etc. 5. Data analysis and visualization applications: introduce the application of data analysis and visualization in the business field, including data analysis methods, data exploration, data mining, data visualization applications, etc. 6. Industry hot topics and trends: Pay attention to industry hot topics and trends in the field of big data visualization, including data security, data privacy, data visualization security, etc. The above was the content that was usually included in the Qinhuang Big Data Visualization Training Course. The specific course content and teaching methods may vary depending on the institution and course.