communicate data insights effectively. 4. Data Cleaning: Cleaning and preprocessing data to ensure accuracy
source, extract, collate, clean and redesign relevant data; queries, cleans & mines large data sets;
design
KPAs:
design
KPAs:
incidents), Information, Clean-up, Importation and Clean-up (Facilitation of data clean-up, Importation of
individual must be comfortable working with Big Data and clean, analyse, interpret, and report back on large data Costing/Pricing for RFQ's and existing clients Data Cleaning & Analytics
database.
to define, design, and ship new features. Write clean, maintainable, and efficient code. Ensure the performance
debugging and documentation. Produce accurate, clean, scalable and maintainable architecture code. Manage