Data Saber

Day after day, we see an increasing number of companies pushing new or upgraded products that are “AI-powered” or “driven by AI”. Meanwhile, every other LinkedIn profile extolls the “data-driven” approaches they and their team took to enhance corporate shareholder value. While I understand the necessity of ensuring your resume ticks off all the buzzword checkmarks, I have to wonder if these people actually understand what it means to be a data-driven organization. “Data-driven” is not a capability. Anyone with a Tableau license can open up a Viz, chuck a few filters on some data, and claim it means anything. No, “data-driven” is a mindset . With any data analysis, the very first step is to decide what story you want to tell . Say that, like me, you want to show how professional translation of website content will generate more clicks and more purchases than machine-translated content.  I think we all generally know professional translation is higher in quality, more effectively loc...

As a linguist with a cultural arts background, my attitude towards process automation had always been somewhat lukewarm. I love to take my time playing with words and exploring the unique elements of each language; “automation” felt like a buzzword for taking the human element out of the art of translation. Technology, however, does not stop progressing, and even the localization industry now benefits from new developments in process automation through advanced software applications known as Translation Management Systems (TMS). These applications utilize powerful algorithms to pre-translate new text based on its similarity to existing text translations in its database; they automatically commit newly delivered translations to that database, creating an ever-growing compendium of translation data that can be smartly reused and recycled; and they even produce reports on quality, efficiency, and overall performance, making it easier for linguists and project managers to understand how tr...

  Completing the Data Saber Program has been an intense affair. Given that most of the contents and learning materials are available only in Japanese, it has stretched my linguistic capabilities to the breaking point. I’m very much on the liberal arts side of language proficiency. I admit that finance, data science, and similar business fields are not my forte (even in English), so I found myself struggling not only to learn a new software from the ground up but also simply to understand at a word-by-word level what was being taught to me. And yet it is for that exact reason I find data visualization to be so powerful, because this program taught me that proper output of visualized data shouldn’t really require second language proficiency. Done right, visualized data is, well, visual. The section on pre-attentive attributes really got me interested. It’s so profoundly intuitive that many people don’t even notice they’re being influenced by these attributes. Of course, the program d...