methods to solve data-related problems.
source, extract, collate, clean and redesign relevant data; queries, cleans & mines large data sets;
and methods to solve data-related problems. Data cleaning, aggregation and the automation of repetitive existing Power BI, Excel, BigQuery etc for tool cleaning, report generation and analysis Finding data quality
design
KPAs:
design
KPAs:
bring ideas to life.
incidents), Information, Clean-up, Importation and Clean-up (Facilitation of data clean-up, Importation of
ensuring accuracy and completeness. Data Cleaning: Pre-process and clean data to prepare it for analysis, which
effectively Data Cleaning:
productivity and quality. Clean Architecture and DDD Implement and advocate for Clean Architecture principles