Course Description
Course Duration: Five Training Days
Course Language: Arabic or English
Include:
Scientific material with TAB
Workshops
Reception and farewell at the airport
Coffee Break
Introduction:
This course on data management, security, and warehousing is tailored for professionals and companies aiming to harness the potential of Big Data effectively. With the emergence of the Big Data phenomenon, businesses increasingly rely on robust Data Analytics and Data Science to address challenges, innovate their operations, and enhance customer service while optimizing costs and streamlining processes. The widespread adoption of these practices has led to the term "Industrial Revolution 4.0" becoming commonplace.
Managing Big Data presents the challenge of efficient data management, which goes beyond mere data acquisition. Data Management involves acquiring, validating, storing, protecting, and processing data to ensure its accessibility, reliability, and timeliness for users.
This course focuses on the crucial aspect of data warehousing, where a multitude of solutions exists. Selecting the right approach poses a significant challenge for companies in the era of Big Data.
Targeted Groups:
- Systems Analysts
- Programmers
- Data Analysts
- Database Administrators
- Project Leaders
- Software Engineers
- Managers
- Professionals involved in Data Analytics
Course Objectives:
Upon completion of this course, participants will be able to:
- Plan the steps in a data warehousing project effectively.
- Understand the escalating need for strategic information.
- Grasp the fundamental concepts of data management and warehousing.
- Implement strategies for data security.
- Utilize appropriate methods and tactics in the Big Data era.
Targeted Competencies:
By the end of this training, participants will be competent in:
- Distinguishing between Operational and Decision Support Systems.
- Extracting strategic information from the Data Warehouse.
- Understanding the significance of Data Management in the Big Data Era.
- Implementing Data Security Strategies for Next-Generation Data Warehouses.
- Executing the Extract-Transform-Load (ETL) Process.
Understanding Data Management, Security, and Warehousing:
This course delves into the complexities of data warehousing management and data management practices. Participants will gain insights into data warehousing and management strategies, optimizing data storage, retrieval, and security.
Course Content:
Unit 1: Agile Enterprise Data Warehousing:
- Agile Manifesto and its principles.
- The Scrum Method.
- Extreme Programming Approach.
- Lean Software Development.
- Sources for Data Warehousing Standards.
Unit 2: Data Security Strategies:
- Trustworthiness assessment of data.
- ISO/IEC 17728 Standard.
- EU General Data Protection Regulation (GDPR).
- Protecting the Data Warehouse.
- Dataset Lifecycle.
Unit 3: Data Warehouse: The Building Blocks:
- Data Warehouse features and characteristics.
- Data Warehouses and Data Marts.
- Overview of Data Warehouse Components.
- Dimensional Analysis of Data.
- Requirements driving Data Warehousing.
Unit 4: Data Warehouse: Architecture and Infrastructure:
- Hardware and Operating Systems.
- Database Software.
- Automation of Warehousing Tasks.
- Data Warehouse Architecture.
- Business Conceptual, Logical, and Physical Data Models.
Unit 5: Data Management, Security, and Warehousing Implementation:
- Data Extraction, Transformation, and Loading (ETL).
- Data Design and Preparation - Data Dimensional Modeling.
- Key Elements of Data Quality.
- User Information Matching.
- On-Line Analytical Processing (OLAP).
- Big Data Processing in Cloud Environments.
Conclusion:
Participants will emerge from this course equipped with a profound understanding of data warehousing management and data management principles. Graduates will receive a valuable data management certificate, validating their expertise in data security and management. Whether seeking data manager training or pursuing data management certification, this course empowers individuals with practical skills to excel in data management roles, ensuring they can effectively navigate the complexities of modern data ecosystems while prioritizing data security.