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Data and Analytics Learner Education Pathway (Level 3)

In this Education Pathway Level, learners complete their foundational Data Literacy journey. It commences with brief examinations of common (yet less understood) topics, including Cloud Computing, Data Modeling, Master Data Management (MDM), and Database Management. Then advances through concise discussions concerning data warehouses and data lakes, and finishes the previous Data Security conversations with an analysis of organizational security issues. The concluding unit of the Pathway explores Data Science technologies and ends with a high-level, albeit more extensive, discussion on Data Strategy.

The Data and Analytics Learner Education Pathway is structured to furnish individuals with fundamental knowledge in data and analytics. Divided into three distinct levels, each pathway offers a carefully selected series of courses that facilitate a progressive understanding of topics commonly encountered within organizations and integral to career advancement.

These Education Pathways cater to anyone seeking a conceptual grasp of data and analytics across diverse domains and disciplines, with the aim of assisting (and possibly challenging) current perspectives and enhancing the effective utilization of organizational information resources.

Each pathway consists of 3.5 – 4.5 hours of course content, complemented by practice exams after each course. Upon completion of the courses within a Pathway, both the individual courses and the entire Education Pathway confer certificates of completion.

**This is Subscription-Only Content, It is NOT purchasable as a separate product**

Data and Analytics Learner Education Pathway (Level 2):

In this Education Pathway Level, learners complete their foundational Data Literacy journey. It commences with brief examinations of common (yet less understood) topics, including Cloud Computing, Data Modeling, Master Data Management (MDM), and Database Management. Then advances through concise discussions concerning data warehouses and data lakes, and finishes the previous Data Security conversations with an analysis of organizational security issues. The concluding unit of the Pathway explores Data Science technologies and ends with a high-level, albeit more extensive, discussion on Data Strategy.

Electives include an examination of NoSQL databases, providing learners with an overview of their functionality and operation. Additionally, there's a course designed to cultivate skills for becoming a data champion within your organization, complemented by a session from Data Governance and Information Quality Conference session around building and keeping engagement with stakeholders.

Each Course Includes:

A 13- to 56-minute educational training video
- Total time: 4:06 hours
A 6- to 14-question review exam
“Check for Understanding” quizzes after each course section
Self-paced and on-demand e-learning
Unlimited course access
Pathway CEUs: 9.0 hours (with electives)

Required Courses within this Education Pathway:

What is Cloud Computing? (Anthony Algmin)
What is Data Modeling? (Anthony Algmin)
What is Master Data Management (MDM)? (Anthony Algmin)
What is Database Management? (Anthony Algmin)
What is a Data Warehouse? (Anthony Algmin)
What is a Data Lake? (Anthony Algmin)
DYBP3: Data Security – Securing Corporate Assets (Jeremy Taylor)
DSBP2: Data Science Technologies (Jeremy Taylor)
DSTR1: Basics for Leadership, Management, and Non-Data Professionals (John Ladley)

Elective Courses within this Pathway:

What is NoSQL? (Anthony Algmin)
BCDM5: Becoming a Data Champion (Frank Cerwin)
DGIQ-E22: Keeping Stakeholders Engaged (Lynn Marsh, Antoinette Cashwell-Robinson, and Lisa McKnight)

Anticipated Data Literacy Proficiency Level: Foundational

At this level, most individuals possess minimal experience in working with data and may lack fundamental comprehension of basic data principles. They might not be acquainted with data types, data concepts, tools for visualizing data, pertinent technologies, or other common data practices, necessitating assistance and training to proficiently leverage data within their responsibilities.

This level of training (within specified Education Pathways) may also be relevant for business professionals, non-technical people, and leadership who want to gain a basic understanding of a given data topic or an overall understanding of a range of data concepts. (e.g. What is Data Strategy and Why Does Our Organization Need One?)

The purpose of this level is for learners to gain:

A fundamental grasp of concepts facilitating effective communication among stakeholders while understanding their role data and analytics usage.
An ability to pose relevant inquiries at the onset of a project, fostering avenues for brainstorming and creativity.

Prerequisites: No course prerequisites or previous expertise necessary.

Technical Coverage: Presents any technical topics around how they affect the business and with clear explanations prior to going into more depth.

Applicable Job Roles/Functions: Foundational learners seeking baseline data and analytics understanding, new staff on-boarding, career development/career change learners, operational employees, data entry staff, front and back-office administrators, contact center teams, and other similar roles.

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