Harnessing the Power of the Data Lakehouse

As organisations continue to collect more diverse data, it is important to consider a strategic & viable approach to unify and streamline big data analytics workloads, ensuring it is optimised to drive data-driven decisions and enable teams to continue innovating...

The Modern Data Stack with dbt Framework

The Modern Data Stack with dbt Framework In today’s data-driven world, businesses rely on accurate and timely insights to make informed decisions and gain a competitive edge. However, the path from raw data to actionable insights can be challenging, requiring a...

The Importance of Feature Engineering in ML Modelling

The Importance of Feature Engineering in ML Modelling When building Machine Learning (ML) models, we often encounter unorganised and chaotic data. In order to transform this data into explainable features, we rely on the process of feature engineering. Feature...

Top 5 Data Engineering Techniques in 2023

Top 5 Data Engineering Techniques in 2023 Data engineering plays a pivotal role in unlocking the true value of data. From collecting and organising vast amounts of information to building robust data pipelines, it is a complex and vital capability that is becoming...