Course Duration ± 16 Hours
“The Data Management Fundamentals course will teach participants the process of organizing, storing, and maintaining data to ensure its integrity, security, and availability for business operations.“
This 2-day Data Management Fundamentals course is designed to provide a comprehensive introduction to the basics of data management, which is the process of organizing, storing, and maintaining data to ensure its integrity, security, and availability for business operations and decision making. The course will cover various aspects of data management, from data governance and quality to data storage and backup, and will also cover data security and privacy, data integration and ETL.
Throughout the course, participants will gain a deep understanding of data management and its importance, and will learn to understand data concepts and terminology. They will learn about data governance and quality, including data governance principles and best practices, data quality and data cleaning, and data lineage and metadata management. They will also learn about data storage and backup, including data storage options such as relational and NoSQL databases, data warehouses, and data lakes, and data backup and recovery strategies.
Participants will also learn about data security and privacy, including data security best practices, data privacy regulations and compliance, and how to identify and mitigate data risks. They will learn about data integration and ETL, including data integration concepts and techniques, Extract, Transform, and Load (ETL) processes, and data warehousing and data lakes. Participants will also have the opportunity to work with real-world data in a case study, which will give them hands-on experience applying data management concepts and techniques to a real-world scenario.
This course is designed for professionals from a variety of backgrounds, including IT, data science, business, and management, who want to improve their data management skills and knowledge. The course is suitable for individuals who are new to the field of data management, as well as those who have some experience but want to gain a deeper understanding of the basics.
By the end of this course, participants will have a strong understanding of data management, and will be well-prepared to organize, store, and maintain data to ensure its integrity, security, and availability for business operations and decision making. They will have the necessary skills and knowledge to govern and ensure the quality of the data, design and implement data storage and backup strategies, ensure data security and privacy and integrate and transform data for analysis and reporting. Additionally, participants will be familiar with best practices and standards for data management, and will have an understanding of the importance of data management in today’s business and technology environments.
This course positions learners to successfully complete the Data Management Fundamentals certification exam.
Course Learning Objectives
The learning objectives of the data management fundamentals course may include:
- Understanding of data management concepts and terminology, such as data architecture, data warehousing, and master data management
- Ability to implement basic data management practices, such as data quality assurance, data normalization, and data standardization
- Knowledge of data governance and data privacy best practices
- Familiarity with data storage and retrieval systems, such as relational databases and NoSQL databases
- Understanding of data integration and data migration techniques
- Ability to design and implement basic data pipelines for data extraction, transformation, and loading (ETL)
- Familiarity with data security and data access control best practices
- Knowledge of data backup and disaster recovery techniques
- Understanding of how to manage and maintain metadata, data dictionaries, and data lineage
- Familiarity with data visualization and reporting tools
The Data Management Fundamentals course is an introductory course for everyone who is involved with data management processes. The target audience for the Data Literacy Fundamentals course includes:
- Junior data engineers and data analysts who want to build their foundation in data management.
- Non-technical professionals who work with data in their daily tasks and want to better understand data management practices.
- IT professionals who want to transition into a data management role or expand their knowledge in this area.
- Business analysts, project managers, and quality assurance specialists who work with data-driven projects and want to understand data management processes.
- Data science students and recent graduates who want to expand their knowledge in data management to improve their employability.
- Individuals who want to develop a basic understanding of data management for personal or professional growth.
Participants to the Data Management Fundamentals course will receive the following study materials:
- 16 hours of instructor-led training and exercise facilitation
- Learner Manual (excellent post-class reference)
- Participation in unique exercises designed to apply concepts
- Sample documents, templates, tools and techniques
- Access to additional value-added resources and communities
Successfully passing (65%) the 60-minute examination, consisting of 40 multiple-choice questions, leads to the Data Management Fundamentals certificate. The examination and certification process is administered by APMG-International on behalf of the Enterprise Big Data Framework Alliance
Detailed Course Outline
Introduction to Data Management
- Overview of data management and its importance
- Understanding data concepts and terminology
Data Governance and Quality
- Data governance principles and best practices
- Data quality and data cleaning
- Data lineage and metadata management
Data Storage and Backup
- Data storage options (relational and NoSQL databases, data warehouses, data lakes)
- Data backup and recovery strategie
Data Security and Privacy
- Data security best practices
- Data privacy regulations and compliance
- Identifying and mitigating data risks
Data Integration and ETL
- Data integration concepts and techniques
- Extract, Transform and Load (ETL) processes
- Data warehousing and data lakes
- Hands-on experience working with real-world data
- Applying data management concepts and techniques to a case study
- Resources and tools for continuing data management education
- Opportunities for further learning and professional developmen
Exam Prep Materials
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