Refreshingly candid review of hurdles to self-service analytics which you should augment by reading "When self-service analytics is a mistake".
The key fact is that self-service BI & Analytics is not an alternative to a well planned, implemented and maintained BI & Analytics commitment across the organisation. That is the necessary precursor to self-service BI.
There is evidence that too many BI deployments are disappointing but the successful ones show how critical and successful they are to commercial enterprises and public sector organisations.
Once successfully deployed, self-service BI is the natural next step to deliver relevant insights across the full spectrum of users from line-of-business operatives to analysts.
Self-service BI is difficult to scale. Self-service BI is typically a great solution for small teams (though these teams may be made up of hundreds of people) and is challenging to scale to the enterprise level. This is because user adoption within BI tends to be low when the BI tool doesn’t have a specific impact and use case for that user. Just having access to a tool without purpose doesn’t work very well. Self-service BI works best when the use case and purpose is clearly defined, which becomes increasingly challenging at the enterprise level. Security is also an issue because scaling self-service BI, without the proper data governance in place, can cause huge security gaps with a company’s data.