Harvard business review recently wrote a wonderful article what a data translator is and why there’s a rising demand for them.
A data translator is an individual that bridges the gap between the analytics and the business team. They aren’t necessarily technically oriented but possess strong domain knowledge along with industry insights.
They play a key role in bridging the technical expertise of data scientists and analytics with the operational expertise of marketing, supply chain or human resource.
Their primary role is to ensure that the analytics derived are of relevance and business significance. By 2026, the McKinsey Global Institute estimates that demand for translators in the United States alone may reach two to four million. Amongst the various skills required for this role are:
However, data translators are difficult to find. This is primarily because there exists no formal certification or diplomas catering to them. Secondly, finding individuals who possess deep industry and company knowledge is difficult. Most companies train or groom existing employees for data translators through apprentice and training programs.
But what if we could solve this issue through AI. Data translators are a valuable and costly resource that is scarce in the market. Through Augmented Analytics, we can use AI to bridge the gap between analytics and operational domains. AI/ML techniques allow business users to directly ask questions or converse with data without requiring a translator!
And all of this is done at a much lower cost, thanks to technology. Companies today can further augment or supplement the skill set of their existing data translators to increase their efficiency and response time.
For more details about Alphaa and how we can enable augmented insights on your existing dashboards, visit www.alphaa.ai