Enhancing Skills for Data Management, Security and Warehousing

Course Overview:

As the Big Data phenomenon appeared Organizations are relying more and more on adequate Data Analytics and Data Science to properly plan, prepare, and react to business challenges, as well as to innovate the way they are conducting their business and increase the level of service to their customers while at the same time reduce costs and streamline their processes. It has become so widespread that the term Industrial Revolution 4.0 become a household name.

With Big Data comes the challenge of data management, as just having the data does not suffice, Data Management is defined as an administrative process that includes acquiring, validating, storing, protecting, and processing required data to ensure the accessibility, reliability, and timeliness of the data for its users. This course focuses on the need to properly warehouse the data as in the era of big data, a wide variety of data warehousing and security solutions exist, and choosing the right approach is the most difficult decision the companies need to make

Course Objectives:

At the end of this course, the participants will be able to:

Learn how to plan the steps in a data warehousing project
Acquire the knowledge to determine why there is an escalating need for strategic information
Get acquainted with the fundamental problem of data management and data warehousing
Learn the strategies for data security
Be able to determine what methods and tactics you should use in the Big Data era

Course Coverage:

Topic 1: Agile Enterprise Data Warehousing:

Agile Manifesto
The Scrum Method
Extreme Programming Approach
Lean Software Development
Sources for Data Warehousing Standards

Topic 2: Data Security Strategies:

How to determine if you can trust your data?
ISO Standard ISO/IEC 17728
EU General Data Protection Regulation (GDPR)
Protecting the Data Warehouse
The Lifecycle of a Dataset

Topic 3: Data Warehouse: The Building Blocks:

Data Defining Features
Data Warehouses and Data Marts
Data Warehouse Components Overview
Dimensional Analysis of Data
Requirements as the Driving Force for Data Warehousing

Topic 4: Data Warehouse: Architecture and Infrastructure Requirements for Data Warehousing:

Hardware and Operating Systems
Database Software
Automation of Warehousing Tasks
Data Warehouse Architecture
Business Conceptual Model
Logical Data Model
Physical Data Model

Topic 5: Data Management, Security, and Warehousing Implementation:

Data Extraction, Transformation, and Loading
Data Design and Data Preparation-data Dimensional Modeling
Key Elements of Data Quality
Matching Information with the User
On-Line Analytical Processing (OLAP)
Big Data Processing in Cloud Environments

Targeted Groups:

Systems Analysts
Programmers
Data Analysts
Database Administrators
Project Leaders
Software Engineers
Managers
Any Professional involved in Data Analytics