A Data Lake is an environment where a vast amount of data of various types and structures can be ingested, stored, assessed, and analyzed. Data Lakes can serve many purposes. …
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.
Big Data Characterized in terms of V’s
Volume: Refers to the amount of data. Big Data often has thousands of entities or elements in billions of records. Velocity: Refers to the speed at which data is captured, …
Data Science – Process and Iterative Phases
The Data Science process follows the scientific method of refining knowledge by making observations, formulating and testing hypotheses, observing results, and formulating general theories that explain results. Within Data Science, …
Data Science – Dependency
Developing Data Science solutions involves the iterative inclusion of data sources into models that develop insights. Data Science depends on: Rich Data Sources: Data with the potential to show otherwise …
Big Data and Data Science – A Glance
Big Data is produced through email, social media, online orders, and even online video games. Data is generated not only by phones and point-of-sale devices, but also by surveillance systems, …
Data Quality – Policy and Metrics
Data Quality – Policy Data Quality efforts should be supported by and should support data governance policies. For example, governance policies can authorize periodic quality audits and mandate compliance to …
Data Quality – As a Part of Data Governance
A Data Quality program is more effective when part of a data governance program. Often data quality issues are the reason for establishing enterprise-wide data governance. Incorporating data quality efforts …
Data Quality Program – Readiness Assessment / Risk Assessment
Findings from a readiness assessment will help determine where to start and how quickly to proceed. Findings can also provide the basis for roadmapping program goals. If there is strong …
Data Quality Program – Implementation Guidelines
Typically, a hybrid approach works best – top-down for sponsorship, consistency, and resources, but bottom-up to discover what is actually broken and to achieve incremental successes. Improving data quality requires …
Data Quality – Audit Code Module and Metrics
Quality Check and Audit Code Modules Create shareable, linkable, and re-usable code modules that execute repeated data quality checks and audit processes that developers can get from a library. If …