Self Service Business Intelligence is a Business Outcome
Self Service Analytics is a Business State — This week we take a look at what self service in Business Intelligence actually means, by looking at what it isn't.
Self service is, after all, notoriously hard to define. To quote a recent blog post by Benn Stancil:
Most definitions of self-serve analytics are both vague and vaguely tautological. TDWI offers a definition without a subject, describing it as “typically involving users throughout an organization to directly access data for self-directed discovery and analysis;” Tableau says it “empowers teams” to “to be more involved in their own data analysis;” and on a page titled “What is self serve analytics?,” Snowflake doesn't even attempt to define it, gestures at some idea about “finessing data,” and describes its pros and cons.
And for good reason: what self service is depends on the org you're talking about. So how to define it when it's so context-dependent?
Staff writer Cedric seems to have found one useful way of thinking about it.
Insights From Elsewhere
Data's Big Whiff — Written by Benn Stancil, and included here for this powerful quote:
The other half of our jobs is doing analysis directly. This work is mostly commonly referred to as ad hoc analysis, though some people call it advanced analytics, or decision science, or just “answering questions.” This is, presumably, what want to do rather than build the dashboards we complain about; we build self-serve tools, we say, so that we can focus on this type of work. Looker sells this promise directly: “Looker helps to streamline processes to save valuable time, freeing up data scientists to focus on the more rewarding aspects of their job.”
We prefer this work in part because it's less tedious than adding the 1,000th filter to a dashboard, and in part because this is the work that actually matters. **Ad hoc analysis is meant to support ad hoc decisions. These decisions are, almost by definition, the most important decisions companies make—they're the ones you only get to make once.* Jeff Bezos' famous one-way doors are the stuff of ad hoc analysis, not a BI report or self-serve dashboard.*
I like this framing very much. Stancil goes on about how ad-hoc analysis isn't saved anywhere and it should be, which you may or may not agree with — but the idea that we should treat ad-hoc queries with the proper respect they deserve is a useful thing to keep at the back of one's head.
Why It's Hard to Teach Data Cleaning — Randy Au on data cleaning as a form of 'ghost knowledge'. The thrust of Au's piece is that data cleaning is a form of analysis, which means that teaching data cleaning is in effect teaching analysis. And teaching analysis is hard.
Building a data team at a mid-stage startup: a short story — Erik Bernhardsson with a piece that's been shared to death in data circles, but linked here because it's kinda sorta related to the Holistics blog post of the week.
So, question: in the following two pictures that Bernhardsson includes in his post, what is the structure that the company uses to get to self-service?
That's it for this week! If you enjoyed this newsletter, I'd be very appreciative if you forwarded it to a friend. And if you have any feedback for me, hit the reply button and shoot me an email — I'm always happy to hear from readers.
As always, I wish you a good week ahead,
Warmly,
Huy,
Co-founder, Holistics.
PS: If you've not seen it already, we've got a guidebook to bring you up to speed on the ins-and-outs of a contemporary analytics stack — get your copy here.