Data and Analytics Learner Education Pathway (Level 1)
In this Education Pathway Level, learners start with a discussion on core topics like Data Literacy and Data Management before progressing through commonly encountered disciplines such as Business Intelligence, Analytics, and Data Governance. Additionally, it introduces learners to the critical aspect of Data Security, relevant to all employees within an organization. The most extensive course in this pathway delves deeper into Data Quality. It covers fundamental knowledge essential for all organization members, regardless of their position or title. This course highlights the significance of Data Quality, its impacts, responsibilities, and outlines actions necessary for ensuring high-quality data assets across the organization.
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 1):
In this Education Pathway Level, learners start with a discussion on core topics like Data Literacy and Data Management before progressing through commonly encountered disciplines such as Business Intelligence, Analytics, and Data Governance. Additionally, it introduces learners to the critical aspect of Data Security, relevant to all employees within an organization.
The most extensive course in this pathway delves deeper into Data Quality. It covers fundamental knowledge essential for all organization members, regardless of their position or title. This course highlights the significance of Data Quality, its impacts, responsibilities, and outlines actions necessary for ensuring high-quality data assets across the organization.
Electives include a short examination of SQL to help non-technical users gain an understanding of what it is and how it works, along with an Enterprise Data World Digital session around building data culture and community.
Each Course Includes:
- A 12- to 62-minute educational training video
- Total time: 4:08 hours
- A 6- to 26-question review exam
- “Check for Understanding” quizzes after each course section
- Self-paced and on-demand e-learning
- Unlimited course access
- Pathway CEUs: 7.5 hours (with electives)
Required Courses within this Education Pathway:
- What is Data Literacy? (Anthony Algmin)
- What is Data Management? (Anthony Algmin)
- What is Business Intelligence? (Anthony Algmin)
- What is Analytics? (Anthony Algmin)
- What is Data Governance (Anthony Algmin)
- What is Data Quality? (Anthony Algmin)
- DYBP1: Introduction to Data Security (Jeremy Taylor)
- MM1: What Is Metadata? (Donna Burbank)
- DQ1: Data Quality Essentials: What Everyone in Your Organization Needs to Know (Danette McGilvray)
Elective Courses within this Pathway:
- What is Structured Query Language (SQL) (Anthony Algmin)
- EDW Digital 23: Building Data Culture and Community (Kiersten Farmer)
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.
Foundations Unit - Complete All Four Courses
1. What is Data Literacy?
required
Data Literacy is about building a collective understanding of the language of data-driven business. It’s about creating a way that we can communicate about data throughout our entire organization. It is a necessary precursor to creating data value, which at its core is the realized difference in costs and risks that we get from using data well versus not using data effectively. It is therefore also an essential piece of the Data Management puzzle.
View Details2. What is Data Management?
required
Data Management is the overarching umbrella around pretty much everything we do with data. It’s the best place to start. This course examines the core concepts of Data Management, including: definitions, why Data Management is essential to organizational success, the value of data as a whole, key Data Management practices, and more.
View Details3. What is Business Intelligence?
required
Business Intelligence (BI) includes the technologies and tools used to analyze and report on different business operations. It typically combines applications and practices for the collection, integration, analysis, and presentation of valuable business information. It is implemented and utilized through best practices to help organizations make more data-driven decisions. Along with recognizing the importance of business analytics, data mining, data visualization, data tools, and data infrastructure, which comprise the foundational principles that collectively govern business intelligence.
View Details4. What is Analytics?
required
Analytics is the established process of inspecting, cleansing, transforming, and modeling data to discover useful information and supporting decision-making. As an effective process for analyzing raw data to find trends and answer questions, analytics encompasses four primary components for operative utilization. Within a broad field, the types of analytics that data specialists rely on consists of descriptive, predictive, and prescriptive. Such methodologies are meant to be employed for information technology, statistics and business efficiency.
View DetailsProgressions Unit - Complete All Three Courses
1. What is Data Governance?
required
The value of Data Governance is only revealed through the use of the data it governs and the behaviors of the people using that data. This course examines the core concepts of Data Governance and its importance to all enterprise data activities, including: definitions, the value of Data Governance from a business perspective, related data topics, common activities, why Data Governance often seems so difficult, and more.
View Details2. What is Data Quality?
required
Data Quality does not simply mean whether or not the data is “right.” It’s much more than that. Data Quality is really about asking how an organization can use information to effectively accomplish a given task and if that data fit for such a use. This course examines the core concepts of Data Quality, including: definitions, a pragmatic understanding, Data Quality dimensions, why organizations need to focus on quality, and more.
View Details3. DYBP1: Introduction to Data Security
required
In this introduction to the basics of Data Security, instructor Jeremy Taylor gives learners a fundamental understanding of the threats, a range of practices, and some security considerations for remote work. This course sets the groundwork for Data Security and covers definitions, types of data, the impact of Data Security on organizations, common Data Security threats, and best practices for individual Data Security.
View Details4. What is Structured Query Language (SQL)?
elective
Structured Query Language (SQL) is set-based language used for managing and interacting with relational databases. It is the most common database management language used today and is employed across a range of use cases and associated technologies throughout organizations worldwide. This course examines the core concepts of SQL, including: definitions, practical uses, why it’s important to understand SQL, key components of SQL, getting started, and more.
View DetailsCompletions Unit - Complete Both Courses
1. MM1: What Is Metadata?
required
Metadata is often seen as an abstract concept. On the contrary, it drives action by adding context and relevance to determine importance. This course sets the stage with a comprehensive discussion of the meaning, significance, and many components of Metadata Management, including business vs. technical metadata, data lineage, impact analysis, relationships, and more.
View Details2. DQ1: Data Quality Essentials – What Everyone in Your Organization Needs to Know
required
It is important to understand that data is a vital asset to be managed and should be managed as intentionally as other assets in your organization, such as people and money. This course covers the basics about Data Quality that everyone in an organization should know – no matter what position or title you hold. Other areas discussed include the definition of Data Quality, why it is important, what impacts the quality of data, who is responsible, and what you can do about Data Quality.
View Details3. EDW Digital 23: Building Data Culture and Community
elective
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