Data Engineering is a data-driven approach to scale the decision-making process and enhance machine learning capabilities. The build system is utilised by data scientists, data analysts, and other specialists to do data collection, data transformation, and data delivering.
Data Integration from internal and external sources in real-time or in batches.
Organise and secure data for governance and compliance.
Monitor and evaluate data quality and performance.
Data Cleaning to enhance its value and usability.
Data Enrichment by matching, cleaning, and augmenting the data.
Customer Data Model to leverage database features, and revamp data quality.
Workflow Management for scheduling, audit, performance, and data quality.
Analyze data analytics, artificial learning, and machine learning.
Serving data to applications, processes, or people aligned with specific needs.
Govern the data catalogues, dictionaries, and mapping.
Data Collection & Integration
Data Storage & ETL/ELT
Data Modernisation & Migration
Data Pipeline
