This month, I am wrapping up my three-part series on evolving data-related roles by focusing on one of the fastest changing and popular roles under discussion in the industry today – the data scientist.
More evolving data-related roles
Last month, I discussed the evolving roles of the Chief Data Officer (CDO), Chief Analytics Officer (CAO), and the Data Engineer. In my blog post this month, I will delve deeper into several of the other roles related to data engineering, as well as the evolution of the role of the Business Analyst.
Examining the continually evolving data-related roles
In my quest to continuously learn more about data-related roles, I have recently come across two very interesting articles that suggest that data-related roles will be changing throughout the remainder of the year. These pieces share some great insight, and I couldn’t resist the opportunity to share my additional views and so in this, the first of a two-part blog series, I will examine the Chief Data Officer (CDO) role, the Chief Analytics Officer role (CAO), and the evolving roles of data engineers.
Dealing with data waste
Previously, I discussed what data waste is and what could likely cause it within an organisation. In the blog, I compared data waste to a box of unused clothes lying rotting up in the attic and the unwanted perils it may cause. In this second blog, the focus turns to how to best deal with data waste by looking at the key components of an effective data waste strategy.
Understanding the causes and risks of data waste
In recent years, there has been a significant focus on individuals and organisations to reduce waste in support of global climate change and environmentally conscious efforts. In my blog post this month, I turn the spotlight on a different sort of waste. This is something which every business around the world struggles with – data waste.
Conference report back: The practical ways data is transforming healthcare
I was fortunate to have been invited to attend the recent ‘Data & Analytics in Healthcare’ conference in Australia which took place at the end of March. The event was positioned as a ‘deep-dive into the data transformation taking place in healthcare across Australia – and aimed to explore efforts to transform the use of data, analytics, and AI in order to deliver great efficiencies and better, more accurate, patient care’. In my blog this month, I will explore whether this was achieved and my key takeaways from the event.
Managing data-centricity during down-sizing
In my blog post this month, I will be discussing how an organisation can stay focused on improving data-centricity even if it is embarking on down-sizing initiatives. It stands to reason that during tougher economic times it is much more difficult to motivate for an upgrade to data-related infrastructure, an increase in staff, or even for advanced training.
How Chief Data Officers can generate and show value
Long-time readers of my blog will know that I’m a great advocate for the Chief Data Officer (CDO) role – and in the right context. This is even more so the case in companies where the CIO has more of a technology focus than a data-oriented one. I was therefore understandably excited by this Harvard Business Review (HBR) article which illustrates how the CDO can demonstrate value inside the organisation.
A deep dive into responsible data and analytics
Having done some work in permaculture and sustainability, I was very interested in this paper that I recently came across entitled ‘Responsible Data and Analytics’. We know that data and analytics can do a lot to enrich our lives, increase productivity, even assist in improving health. But if done incorrectly, or deployed irresponsibly, it can also ruin businesses, lead to great failures, expose private details, and cost lives.
