Data and Analytics Talent

A common consensus amongst industry leaders is that there is a data professionals drought. The term ‘data professional’ covers three roles that operate in what constitutes the data life cycle: Data Engineer, Data Analyst and Data Scientist. However, by digging deeper into the current hype of one of the hottest jobs around, the reality shows an imbalance chasm in demand, most glaringly in not knowing what type of data professional is required. This points to a shallow awareness of the components necessary to become a data-driven organisation.

At CADS, analytics are not treated as merely a project but part of the DNA of organisations wherein all decisions are made based on facts and insights. In fact, in today’s world, actionable insight is considered a realm of machine learning. Taking stock of where you are as an organisation helps identify the talent and resources needed to become data-driven while staying competitive and relevant.

Our existence is based on solving this conundrum. We have conceived a Training Framework to support knowledge development for roles within the data analytics eco-system in line with the data life cycle. Our framework starts with data management and data governance through to data analyst, data science, Machine Learning and Artificial Intelligence. The framework is designed to support training, upskilling and re-training.

To upskill existing or fresh graduates, we recently launched the Data Star program to train graduates in the field of data engineers, analysts and science. Carefully selected students will spend two months trained in their respective fields comprising lectures and hands-on exercises with our data scientists. The training period is followed by a four-month management training program where the students must complete data and analytics-related projects with major organisations. Students are also required to return during the four-month period to attend soft skills training and lab days where they are encouraged to consult our data scientists.

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