// SCALING UP //
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WE BUILT A NUMBER OF ALGORITHMS WHICH WE PUT INTO A PRODUCT , ALL USING
DATABRICKS TECHNOLOGY AT ITS CORE , WHICH IDENTIFY POTENTIAL RISK
IN PLAYERS . the legislation is asking us to look at . Secondly , we spend a lot of time with clients in this area but again in the background , so we work really closely with the teams within our clients , especially within the safer play area .
Finally , with something like the review of the UK Gambling Act , for example , we spent a lot of time internally thinking about , what ’ s our view on that because we spend a lot of time in this area , we ’ ve got a lot of experience in this area so we formulated quite a detailed response to the call for evidence on the legislation and we ’ ve submitted that as part of the call for evidence into the review
Why is prioritisation of culture the key enabler for cutting edge data products and solutions ?
This is probably one of the most used and potentially overused words in any business and given how the whole agile methodology transitioned into most mainstream businesses over the last 10 years , I ’ m sure there is a business that doesn ’ t even have a computer at the moment – they are still talking about prioritisation . Clearly , with great power comes great responsibility but with great technology comes great opportunity .
When I ’ m thinking of a really important prioritisation for me , I just go back to my first-year economics textbook . And one of the biggest principles in economics is opportunity cost .
With a business like ours , we could build loads of new features , loads of new models . We ’ ve been talking about product in the business at the moment and a mantra of product market fit – you only build things that people actually want . With any tech business , prioritisation is probably the most important thing to do . Again , just always go back to the opportunity cost , every decision to do X is a decision not to do Y .
The other big opportunity cost you have is people ’ s time . It ’ s not just about prioritising which product feature you focus on . When I think about prioritisation , it genuinely goes down to ‘ does that data scientist need to be in that meeting ’ because an hour in that meeting is an hour not spent coding . �
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