Data Quality Improvements – Assessing the Current State In order to improvements the Data Quality, DQ Analysts must have the clear picture about Current State of Data Quality as well …
As an accomplished professional with a Master Degree in Computer Science (Specialization in Software Engineering) and a PGD in Management Information Systems, over 20 years of hands-on experience in Information Technology, Data Governance, Data Management, and PDPL plus NCA Compliance. Expertise spans diverse sectors, including Aviation, Healthcare, Investment, Education, and Construction, allowing me to effectively bridge the gap between technical and business needs.
Leadership roles include Manager – Data Management (DMO), Manager Systems, Sr. Team Lead – Data Specialist, Manager Applications, and Adjunct Faculty Member among others. I am also deeply involved in applied research, focusing on Big Data Governance, Privacy, Security, and Compliance. My work has been published in prestigious international journals, offering valuable insights into solving industry challenges.
Possesses extensive expertise spanning a diverse range of platforms, tools, technologies, hardware, software, and operating systems, effectively leveraging this knowledge to address complex challenges in Data governance, security, privacy and compliance.
With 45+ professional certifications, including Certified Data Management Professional (CDMP), GDPR, CCPA, Certified Data Protection Officer (CDPO), ITIL, EC-Council Disaster Recovery Professional, AWS Cloud Certified, Oracle Technologies including e-Business, Databases, and Oracle Cloud Infrastructure (OCI). I have continually enhanced my expertise in the ever-evolving field of data privacy and security. My competencies also include Disaster Recovery, Business Continuity, Regulatory Compliance (GDPR, NCA, CCPA, NDMO), Data Architecture, Metadata Management, and more.
Numerous initiatives in Data Governance, Data Management, Data Privacy, Data Protection, ensuring compliance with international, and local standards such as NCA, GDPR, KSA PDPL, and NDMO.
Data Quality Assessment
Data Quality Assessment – A Practical Approach to Improvement DQ Analysts will need to sort out and prioritize findings. The goal of an initial Data Quality Assessment is to learn …
RDM – Reference Data Management
What is RDM – Reference Data Management Reference Data is any data used to characterize or classify other data, or to relate data to information.Reference Data Management entails control and …
Data Management – What is Master Data?
What is Master Data Management-MDM Different types of Data play different roles within an organization. They also have different management requirements. Malcolm Chisholm has proposed a six-layer Taxonomy of Data …
Reference and Master Data Management – Guiding Principles
Shared and Owned Enterprise Data in Master Data Mangement Principles Stewardship and Data Quality Governance Change Control and System of Record in Master Data Mangement Principles
Data Quality – Parsing and Transformation
How Data Quality Work in Parsing and Transformation Data Quality Parsing Data Parsing is the process of analyzing data using pre-determined rules to define its content or value. Data parsing …
Data Quality – Cleansing and Enrichment
Data Cleansing Data Cleansing / Scrubbing Data Cleansing or Scrubbing transforms data to make it conform to data standards and domain rules. Cleansing includes detecting and correcting data errors to …
Data Quality – Data Profiling
What Is Data Profiling in Data Quality? Data Profiling is a form of data analysis used to inspect data and assess quality. Data profiling uses statistical techniques to discover the …
Data Quality – Causes of Data Quality Issues – Part-03
Data Quality Issues Part-03 Issues Caused by System Design Failure to Enforce Uniqueness Constraints Multiple copies of data instances within a table or file expected to contain unique instances. If …
Data Quality – Causes of Data Quality Issues – Part-02
Resolving Data Quality Issues Part 02 Issues Caused by Data Entry Processes Data Entry Interface Issues Poorly designed data entry interfaces can contribute to data quality issues. If a data …