{"id":1551,"date":"2023-05-24T01:38:41","date_gmt":"2023-05-23T17:38:41","guid":{"rendered":"https:\/\/digitspark.co\/blog\/%e3%80%90%e8%ae%80%e6%87%82%e6%95%b8%e6%93%9a%e3%80%91%e4%ba%ba%e4%ba%ba%e9%83%bd%e8%a6%81%e6%9c%89%e7%9a%84%e6%95%b8%e6%93%9a%e7%b4%a0%e9%a4%8a%ef%bc%9a%e6%95%b8%e6%93%9a%e6%ba%9d%e9%80%9a\/"},"modified":"2025-12-13T06:28:59","modified_gmt":"2025-12-12T22:28:59","slug":"%e3%80%90%e8%ae%80%e6%87%82%e6%95%b8%e6%93%9a%e3%80%91%e4%ba%ba%e4%ba%ba%e9%83%bd%e8%a6%81%e6%9c%89%e7%9a%84%e6%95%b8%e6%93%9a%e7%b4%a0%e9%a4%8a%ef%bc%9a%e6%95%b8%e6%93%9a%e6%ba%9d%e9%80%9a","status":"publish","type":"blog","link":"https:\/\/digitspark.co\/en\/blog\/%e3%80%90%e8%ae%80%e6%87%82%e6%95%b8%e6%93%9a%e3%80%91%e4%ba%ba%e4%ba%ba%e9%83%bd%e8%a6%81%e6%9c%89%e7%9a%84%e6%95%b8%e6%93%9a%e7%b4%a0%e9%a4%8a%ef%bc%9a%e6%95%b8%e6%93%9a%e6%ba%9d%e9%80%9a\/","title":{"rendered":"[Understanding Data] Data Literacy Everyone Should Have: Data Communication"},"content":{"rendered":"

#DataReading #DataLiteracy #DataCommunication<\/span><\/h1>\n

Essential Data Literacy for Everyone: Data Communication<\/span><\/h2>\n

In this article<\/span><\/a>\u00a0, we\u00a0emphasized that “everyone needs to have data literacy” and mentioned that everyone has different specializations in a company; however, there is one\u00a0<\/span>ability that “everyone must have<\/span><\/strong>\u00a0“:\u00a0<\/span>data communication<\/span><\/strong>\u00a0.<\/span><\/p>\n

Simply put, “data communication” means: taking the data I have, organizing and analyzing it, and presenting it in the most straightforward way so that others can understand it, comprehend it, and even provide feedback.<\/p><\/blockquote>\n

Here, “I” can refer to everyone in different positions within the company. “Others” refers to the people I need to communicate with in different situations.<\/span><\/p>\n

For example,\u00a0<\/span>an Account Manager (AM)<\/span><\/strong>\u00a0might need to report to a client on the new traffic generated by SEO this quarter, or an AM might find that a client’s platform conversion rate is unstable and want to work with the company’s analysts to adjust the screening criteria for acquiring new members. In both of these scenarios, “I” am the AM, but the communication focus, expected goals, and target audience are different, and therefore, the data “I” need to present will also differ. To achieve effective communication, “I” cannot simply state the data as “The X index increased by 20% in Q1, which is four times higher than the previous quarter,” but rather\u00a0<\/span>explain the significance to the target audience in a more specific way<\/span><\/strong>\u00a0.<\/span><\/p>\n

\"\u6578\u64da\u6e9d\u901a\"Image source: Internet<\/p>\n

For example, an Account Manager (AM) can explain to clients based on data results: “The 20% increase in the X index is due to changes in consumer behavior or actions during Q1…” or report to analysts: “What aspects of the X index are important to clients? What other data do they need to clarify their issues?” etc. By leveraging their professional knowledge, they first identify the “data collected over a period of time and its significance,” and then visualize and\u00a0<\/span>organize it<\/span><\/a>\u00a0. This allows them to easily convey the meaning of the data and the specific tasks to be done next when communicating with others.<\/span><\/p>\n

Have you noticed? To master data communication,\u00a0<\/span>“descriptive analysis” and “diagnostic analysis”<\/span><\/a>\u00a0are essential. Across the four levels, these two skills are skills that everyone, except for corporate decision-makers, should be trained to promote the smooth operation of various internal and external collaborations within the company.<\/span><\/p><\/blockquote>\n

What data skills are hidden among the various types of people in a company?<\/span><\/h2>\n

If we dissect Digit Spark as a data “marketing” company, there are various functional positions. Apart from “decision-makers,” they can be simply divided into four teams: “Information Technology,” “Marketing,” “Sales,” and “Administration.” Let’s take a look at how everyone usually interacts with “data.”<\/p>\n

\"\u4f01\u696d\u5167\u7684\u6578\u64da\u8077\u80fd\"<\/p>\n

Information Technology<\/span><\/h3>\n

AI tool development engineers and data scientists primarily work to\u00a0<\/span>invent applicable AI and Martech tools<\/span><\/strong>\u00a0for businesses. Skills include:<\/span><\/p>\n