What key skills or attributes do you consider have contributed to your success in your current role?
First, we have 30 years of practical experience including an analytics and AI start-up as well as leading large businesses in two global firms. Even so, we are continuously learning about users’ missions, relevant technology changes, opportunities and risks and staying close enough to the actual work content to understand the challenges and potential pitfalls. It is essential to continually learn even as you transition from daily work at the keyboard to leading teams and larger efforts.
What level of data maturity do you typically encounter across your client base and what tends to hold this back?
Tremendous variation is normal and expected. Consider the range of executives and leaders. Some are deeply expert in the mission, but not in technology. Some bring great depth in enterprise technology, but are learning regarding AI and the connection to data. Overall, in the past five-to-ten years the awareness of importance increased noticeably. Getting beyond that to actions is a separate issue.
What trends are you seeing in terms of the data and analytics resources your clients are demanding from you?
Integrative technologies to increase data accessibility, with appropriate security controls, to support a range of functions. This can take the form of important middleware like MuleSoft or quite sophisticated solutions like Immuta. Separately, clients crave integrated technologies which enable the deployment of machine learning and artificial intelligence. Examples here include solutions like Dataiku (which opens many pathways to various software while accessing data) or Databricks which takes its well-established functionality and innovates by bringing capabilities like its Dolly Large Language Model.
