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Artificial Intelligence Specialist

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Module 1: Fundamental Data Science Governance
for Big Data, Machine Learning & AI

This course describes data science governance concepts and basics and identifies common risks and challenges, as well as key roles for those involved in governance projects. The course further explores the analytics pipeline governance lifecycle and establishes over 70 data science governance precepts and processes. The course maps how precepts and processes relate to each other and how they relate to governance stages.

A few examples of the many precepts and processes covered in this course are provided here, in relation to their corresponding governance stages:

  • Business Case Evaluation (including Organizational Maturity Assessment, KPI Definition, etc.)
  • Data Identification (including Dataset Metadata Template, Data Source Categorization, etc.)
  • Data Ingress (including Data Volume & Velocity Threshold, Ingress Logic Version Control, etc.)
  • Data Storage – Raw (including Data Lake Formation, Data Provenance & Lineage Template, etc.)
  • Data Cleansing & Validation (including Data Model Definition, Data Inconsistency Notification, etc.)
  • Data Tagging (including Data Class Taxonomy, Data Classification Automation, etc.)
  • Data Sanitization (including Data De-identification Template, Data De-identification Logic Centralization, etc.)
  • Data Transformation (including Input & Output Data Models, Data Transformation Cost Analysis, etc.)
  • Data Storage – Processed (including Data Warehouse Formation, Data Access Metering, etc.)
  • Data Analysis (including Analysis Services Enablement, Visualization Access Control, etc.)
  • Data Utilization (including Insights Sensitivity Classification, Visualization Change Management, etc.)

Relevant roles are also mapped to individual governance stages.

Taking the Course at a Workshop

This course can be taken as part of instructor-led workshops taught by Arcitura Certified Trainers. These workshops can be open for public registration or delivered privately for a specific organization. Certified Trainers can teach workshops in-person at a specific location or virtually using a video-enabled remote system, such as WebEx.

Visit the Workshop Calendar page to view the current calendar of public workshops.

Visit the Private Training page to learn more about Arcitura’s worldwide private workshop delivery options.

Taking the Course via an eLearning Study Kit

This course can be completed via self-study by purchasing an eLearning study kit subscription, which includes online video lessons, as well as online and offline access to the electronic course materials and additional supplements and resources designed for self-paced study and exam preparation.

Visit the eLearning Study Kits page for more information about eLearning study kits.

Visit the Arcitura online store for purchasing information.

Taking the Course via a Printed Study Kit

This course can be completed via self-study by purchasing a printed study kit, which includes the full-color course materials as well as additional supplements and resources designed specifically for self-paced study and exam preparation.

Visit the Printed Study Kits page for more information about full-color printed study kits.

Visit the Arcitura online store for purchasing information.


This course is one of three courses that are used to prepare for Exam DG90.01. A passing grade on this exam is required to achieve the Data Science Governance Specialist certification.