There are several ways of measuring a data model’s quality, and all require a standard for comparison. One method that will be used to provide an example of data model …
Master’s degree in computer science with Specialization in Software Engineering and Earned PGD in Management Information System. Accumulated 20+ years’ Information Technology, Data Governance, Data Management, and Compliance related consecutive hands-on experience, possess diversified business and technical background across the Aviation, Healthcare, Investment, Education, and Construction sectors.
45+ Online Professional Certifications, which includes:
• CDMP – Certified Data Management Professional
• CDPO – Certified Data Protection Officer
• GDPR – General Data Protection Regulation Practitioner
• EDRP – EC-Council Disaster Recovery Professional
• AWS Certified Cloud Practitioner
• Oracle Enterprise Data Management Professional
• Oracle Database Cloud Certified Professional
• ITIL – Information Technology Infrastructure Library (ITSM – IT)
Experience includes leading data governance and management initiatives, ensuring compliance with NDMO, GDPR and KSA PDPL, and implement/improve data security, privacy, & protection. Expertise spans a wide variety of platforms, tools, technologies, hardware, software, and operating systems.
Served in leadership capacities such as Manager – Data Management, Sr. Team Lead – Database Specialist, Sr. Team Lead Consultant, Sr. Applications DBA, Sr. Resident Consultant, and Manager Systems.
Data Modeling – Deliverables
The Deliverables of the Data Modeling Process include: Diagram: A data model contains one or more diagrams. The diagram is the visual that captures the requirements in a precise form. …
Normalization
Normalization is a Systematic Approach, which is used to design a Relational Database table up to higher normal form. The basic goal of normalization is to keep each attribute in …
Data Modeling – De-Normalization and Canonical Model
De-Normalization is the deliberate transformation of normalized logical data model entities into physical tables with redundant or duplicate data structures. In other words, de-normalization intentionally puts one attribute in multiple …
Content Management – Terms Management
As per DAMA, Lists of terms are just that: lists. They do not describe relationships between the terms. Pick lists, web pull-down lists, and lists of menu choices in information …
Data Modeling – Identifiers / Keys
Key or Identifier, is a set of one or more attributes that uniquely defines an instance of an entity. Keys by Construction-Type Surrogate Key is a unique identifier for a …
Content Modeling – Controlled Vocabularies and Format
Controlled Vocabularies The primary purpose of Vocabulary Control is to achieve consistency in the description of content objects and to facilitate retrieval. A Controlled Vocabulary is a pre-defined, established and …
Data Modeling – Arity of Relationships
Arity of RelationshipsThe number of entities in a relationship is the Arity of the relationship. The most common Arities are unary, binary, and ternary relationships. Unary (Recursive) Relationship: A unary …
Data Masking – Data Subsetting
Data Masking is the process to replace, truncate, scramble, or encrypt sensitive data with fictitious yet realistic looking. Data Masking limits sensitive data proliferation by anonymizing sensitive production data. Data …