The Data Consumer Spectrum Paid Members Public
As a data leader, it is important to know your audience. They are the people consuming your data products and using them, hopefully, to make better decisions. Their preferences extend beyond the substance of what you provide them, to how they consume that data, in what quantity, and how much
What Makes A Good Data Leader? Paid Members Public
This is not an article about how to be a good leader; there are many great examples and perspectives on that broader topic elsewhere. This is an article outlining what I believe are the qualities that make a good data leader; both good for their team and good for their
How AI Can Help With COVID-19 Paid Members Public
The global coronavirus pandemic has led to unprecedented scenarios in almost all aspects of life, throughout the world. A battle to reduce the spread of infection, keep mortality low and maintain both economic activity and public order requires critical decision making in highly ambiguous spaces. This pandemic is also the
AI: A Team Effort Paid Members Public
With the explosion of interest in AI across businesses of all kinds, particularly in traditional industries, the emergence of new platforms and solutions have helped make AI more accessible. The latest versions of frameworks like TensorFlow [https://www.tensorflow.org/] and PyTorch [https://pytorch.org/] have made model building more
Permission To Land: Ensuring Analysis Has Value Paid Members Public
At the heart of it, the purpose of analysis is to drive better actions through informing better decision making. In this article, I will focus on one of the most important parts of this process; making sure the output lands well and drives action. When is the right time to
What To Look For In A Data Leadership Role Paid Members Public
A few months back, we shared a series of articles to help analysts and data scientists choose their next role (parts 1 [https://qstar.ai/analysts-data-scientists-how-to-choose-your-next-role-part-1-of-4/] , 2 [https://qstar.ai/analysts-data-scientists-how-to-choose-your-next-role-part-2-of-4/] , 3 [https://qstar.ai/analysts-data-scientists-how-to-choose-your-next-role-part-3-of-4/] and 4 [https://qstar.ai/analysts-data-scientists-how-to-choose-your-next-role-part-4-of-4/] ). Here, I expand on t
Embed Or Centralise? Where To Build Your Analytical Capabilities Paid Members Public
When a business reaches the point when it decides it needs dedicated analyst or data science capabilities, one of the first questions that gets asked is ‘where should we put it’? There is no universal answer but there is another question that serves as a good starting point; should the
Analysts & Data Scientists, How to Choose Your Next Role (Part 4 of 4) Paid Members Public
Part One [https://qstar.ai/analysts-data-scientists-how-to-choose-your-next-role-part-1-of-4/] | Part Two [https://qstar.ai/analysts-data-scientists-how-to-choose-your-next-role-part-2-of-4/] | Part Three [https://qstar.ai/analysts-data-scientists-how-to-choose-your-next-role-part-3-of-4/] | Part Four Welcome to the final part of our four-part series on choosing your next data science or analytics role. We have covered a lot of ground so far: from choosing the
