Comprehensive Guide to Data Management, Security, and Warehousing

Introduction:

The Comprehensive Guide to Data Management, Security, and Warehousing course is designed for individuals and organizations aiming to harness the full potential of Big Data. As companies increasingly rely on Data Analytics and Data Science, this course addresses key challenges, transforms processes, and enhances customer service, while also aiming to reduce costs and boost efficiency. The course's relevance has grown with the rise of the Industrial Revolution 4.0, underscoring its importance in the current data-driven era.

Effective data management involves more than just possessing data; it requires a comprehensive organizational approach that includes data acquisition, validation, storage, protection, and timely processing to ensure accessibility and accuracy for users.

This course emphasizes the significance of addressing data warehousing issues in the Big Data age. With numerous data warehousing and security solutions available, selecting the most suitable approach is a critical decision for organizations looking to enhance their data management systems.

Objectives:

By the end of this Comprehensive Guide to Data Management, Security, and Warehousing course, participants will be able to:

• Understand the phases and stages of data warehousing development.
• Recognize the growing importance of information in organizations.
• Identify key issues in data management and warehousing.
• Implement appropriate data protection measures.
• Apply effective methods and approaches in the Big Data era.

Training Methodology:

• Instructor-led courses
• Case studies
• Group work
• Mock-ups

Course Outline:

Unit 1: Agile Architecture in the Data Warehouse Industry

• Expectations of Agile
• Scrum Method
• Extreme Programming Approach
• Lean Software Development
• Conformance Databases in Data Warehousing

Unit 2: Data Security Approaches

• Evaluating data adequacy
• ISO/IEC 17728
• European Union General Data Protection Regulation (GDPR)
• Data Warehouse Security
• Dataset Lifecycle

Unit 3: Data Warehouse: The Building Blocks

• Defining data features
• Data Warehouses vs. Data Marts
• Overview of data warehouse components
• Dimensional Modeling of Data
• User Requirements Driving Data Warehousing

Unit 4: Data Warehouse: Architecture and Infrastructure Requirements

• Computer hardware and Operating Systems
• Database Software
• Automation of Warehousing Procedures
• Data Warehouse Framework
• Conceptual Business Model
• Logical Data Model
• Physical Data Model

Unit 5: Data Management, Security, and Warehousing Process

• Data Pull Paper and Transformation, Data Loading
• Data Structure and Preparation using Dimensional Modeling
• Insights from Gephart, 2012
• Data Quality Types and Characteristics (Clarke, 2003)
• Current OLAP Usage Examples
• Utilization of Cloud Computing for Big Data Processing