Ten Data Challenges We Face With COVID-19 (Pt. 2) Paid Members Public
The past week has been marked by differing levels of government responses. While some announced decisive policies, others went back and forth [https://www.bbc.com/news/science-environment-51892402] on the most appropriate course of action. Since COVID-19 was first acknowledged in December 2019 more than 10,000 people are confirmed
Ten Data Challenges We Face With COVID-19 (Pt. 1) Paid Members Public
On March 12 the WHO announced [https://www.bbc.com/news/world-europe-51876784] that "More cases are now being reported every day than were reported in China at the height of its epidemic," marking a new phase of the Coronavirus pandemic. Every day there seem to be more numbers
Why Your Analytics Transformation Needs Help From HR & Communications Paid Members Public
Those of you that I have worked with before know that I have a soft spot for HR and Corporate Comms. Not only are these teams often overworked and under resourced, but they tend to be staffed with some of the most engaged and empathetic colleagues you will meet. To
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
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
Data Product Managers, Not Just Project Managers Paid Members Public
As we reviewed last week [https://qstar.ai/elements-of-an-effective-data-analytics-function/], building an impactful data, analytics, and AI capability requires a range of new roles and competencies. While the scope and responsibilites of roles such as data quality analyst or data architect are usually easy for the business to grasp, data product