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The Analytics Translator - Data Science Career Development
Rating: 3.9 out of 5(69 ratings)
445 students
Created byFrank Kienle
Last updated 2/2024
English

What you'll learn

  • A better understanding of the role analytics translator and the link between Business, Analytics, and IT
  • The content should illuminate the difference to data science and the challenges within the job role of an analytics translator.
  • Support your personalised curriculum of the learning journey by a better understanding the connected terminology between multiple subjects.
  • Part II: Generative AI overview and applied uses cases

Course content

23 sections56 lectures4h 3m total length
  • 1.1 Lecture Goal2:56
  • 1.2 Procedure1:04
  • Possible Practices0:16

Requirements

  • Open to learn and hear aspects from other domains
  • Self-learning capabilities and endurance to learn the full picture
  • Critical rethinking capabilities on pre-defined learning journeys and simple answers.

Description

The role of analytics translator is not well defined, yet, an exciting, challenging, and emerging role for a future job profile.


Part I Gives an overview of 15 key capabilities that fall into the analytics, business, and IT know-how class to master the role of an analytics translator.

Part II (new update Oct 2023) delves deep into what the future holds for our workplaces, shining a light on the latest trends of generative AI and its use cases for the analytics translator.


Each learning path is different, and multiple topics and skills contribute to this job role. The content should illuminate the difference between data science and the vast learning possibilities within the job role of an analytics translator.

Thus, the goal is to drive your personalized curriculum of the learning journey by a better understanding of the connected terminology between other subjects.

The mission of the lecture: judge better on your analytics translator learning journey.


Analytics translators have the vital goal of integrating analytics capabilities in a company.

  • They identify value cases for the business that analytics can help solve.

  • Lead or support data science and IT teams in developing data-driven solutions to these problems.

  • They ensure the usage within business operations.

  • They have to be front runners in embedding new technologies like generative AI :-)


The top domains for an analytics translator are fluent speaking and understanding business know-how, IT constraints, and analytics understanding.


The lecture derives from practical insights in strategically embedding this role in global digital transformation initiatives.

Who this course is for:

  • Every person who is interested in the role of an analytics translator.
  • Students during their studies hearing the 'analytics translator' role and want to know more
  • Persons moving into this job role
  • Persons in organizations launching business analytics teams and digital transformation
  • Persons interested how to embed generative AI in the work flow