Automating analytics – managing the people-to-machines handover
Data scientists cost a lot of money. Data analysts are in short supply. But faster, more accurate models are in growing demand to support everything from decision science to HR. So how can organisations resolve this imbalance?
One solution is to deploy machine learning and automation against the very process of analytics itself. In many areas, model building relates to routine, repeating activities that can be mapped and standardised. Even the supporting data flows can be automated within established parameters, reducing the need for human intervention significantly.
So what stands in the way of apply automation in this area? Is there a lack of political will to tackle headcount and overheads? Or do the potential solutions still lag behind? This roundtable will hear what works and what doesn’t when trying to convert human actions into machine ones.
- Data Science, Decision Science, Data Analytics
Who should attend?
- Chief analytics officers and data scientists who are applying machine learning to internal analytics processes, from data extraction and annotation to model building
- Chief data officers with responsibility for headcount, hiring and role-setting looking at how to optimise their department
Why should you attend?
- Learn from other practitioners and share your experiences within your peer group
- Create new contacts with other DataIQ members, extend your professional network into the wider community
- 1 hour, digital roundtable delivered via Zoom
- Closed forum, open discussion, recruiter and vendor free, Chatham House rules
- Small and focused group of senior data leaders
To register for this event, simply email Steph below and joining instructions will be sent to you directly. Please be aware there are only limited places available on a first come, first served basis.