Data strategy is the cornerstone of any data driven organisation. Without strategy, insight and ROI are hard to achieve.

Once the strategy is defined, data needs to be cleaned, transformed and enriched. We do that through data engineering.

Once data is engineered, it’s ready to pipe into a machine learning algorithm to provide competitive advantage.

Data Strategy

The key component of any successful data driven company.

This section outlines what should be included in your data strategy & links out to our other content to support those suggestions.

Data Engineering

Extract, Transform, Load, Visualise are the 4 components of data engineering. We've included some Python & Spark code samples.

Data Engineering

Extract, Transform, Load, Visualise are the 4 components of data engineering. We've included some Python & Spark code samples.
View

Data Science

Machine learning is having a profound impact on many businesses. We discuss the concept & provide Python code samples.

Data Science

Machine learning is having a profound impact on many businesses. We discuss the concept & provide Python code samples.
View

E-Books

There are three Kodey e-books available:

AWS Zero to Hero , written in 2017 takes you through the key architectural concepts around AWS.

Let’s Do Hadoop (2018), takes you through the key architectural concepts in the world of Big Data.

DataGov is a short book written in 2019 covering some of the key principles of data governance.