What is data literacy?

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It refers to the logical ability to read and understand data, look at a problem, analyze it from various perspectives, and reach a solution to the problem. As technology becomes increasingly sophisticated, data literacy is becoming more and more important in order to use data to make data-driven decisions rather than relying solely on intuition. Actions that reduce the probability of failure and increase the probability of success by making better choices in diagnosing problems correctly through data, understanding trends and relationships with users, and deriving hypotheses to solve problems and drawing conclusions to solve corporate or social problems. It is the ability to find evidence directly in the data. Why data literacy is important (and necessary) It is no exaggeration to say that data has driven enormous innovation in business and society in recent decades. By using data, companies can establish industry strategies, improve performance, and gain competitive advantage over competitors through data-driven decision-making rather than individual intuition.

Data literacy, which refers to data literacy, does not require Canada Phone Number Data tremendous expertise, but it is increasingly considered an important competency for decision-makers and practitioners who are exposed to indiscriminate information and the era of data flooding. Examples of causal and correlation errors From the perspective of a search advertising practitioner, he or she may become immersed in data to find the causal relationship between conversion figures and search advertising, while a CRM marketing practitioner may use data, numbers, or visualization to find the causal relationship between CRM marketing actions and conversion figures. You can become immersed in the two rising curve graphs. If you do not have the ability to objectively analyze data, that is, data literacy, it will be difficult to distinguish the exact cause-and-effect relationships and correlations in small numbers or dashboard graphs, making it impossible to see the correct problem or plan a solution. Understanding the Data Ecosystem Data literacy refers to the ability to read data and understand the hidden meaning within it, as well as the ability to communicate it. It has a comprehensive meaning that includes not only how to read data, but also the capabilities of data processing, analysis, planning, and visualization. Understanding the data ecosystem provides a glimpse into how skills are segmented for data literacy capabilities.




Harvard Business School Each organization will have its own data ecosystem. Harvard Business School classified the ecosystem into stages where each of the eight actions is possible, and divided the eight steps as follows. 8 steps to data ecosystem Generation – Generation Collection – collection Processing – Processing Storage – storage Management – ​​Management Anaysis – Analysis Visualization – Visualization Interpretation – Interpretation The reason why the data ecosystem is circular like that is because data creation starting from a project is interpreted through a process, and the final step of interpretation ultimately leads to the start of another project. It depicts an infinitely repeating cycle in which new work is done through new goals and new learning, that is, through data-driven decision-making. How to Improve Data Literacy Skills Just as an individual's logic and literacy cannot improve dramatically in a short period of time, data literacy cannot be completely acquired in an instant, but data literacy can be gradually increased through several attitudes and attitudes in everyday life or when dealing with work. 1. Looking at it from an opposing perspective Having opposing perspectives expands our thinking beyond our perspectives and ingrained prejudices.