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
Beware Tech Advocates Bearing Certainty Paid Members Public
Many organisations are forced to take a leap of faith. Under pressure from consumers or shareholders they know they need to transform, but they might not have the comprehension, capability, or capacity yet to guarantee the success of such a move. Yet they must jump! This is particularly true when
How Did Enterprise Data Science & AI Fare in 2019? Paid Members Public
This is the time of year where many of us find ourselves reflecting on our performance. Did we stick with those New Year's resolutions, or not? Did we achieve what we wanted to achieve, or not? Similarly, let us consider how data science and AI fared in the
'Twas the Post Before Christmas (2019 Edition) Paid Members Public
'Twas the post before Christmas, fifty-two on this blog, It was due this morning, but Ryan slept like a log; Yet this seems a good time, for the year to review, In hopes of sharing some useful insights with you; First off, I can say, with a degree of
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
When Not to Use Analytics Paid Members Public
In my fifty weekly posts so far this year, almost every single one has advocated for the application of analytics and artificial intelligence (AI). While this is often the most sensible course of action, it is just as important to consider when not to use data. As they say: if