Yeah, I am nervous about it. You're now empowering people to go do all this stuff, but the world isn't that easy. Really the world is really complicated and you can't do that at such a higher level of abstraction.
Cindi:
Okay, but I have to push back here.
I do think it's like, "What's the right application?" But are you letting your fear override and squander the potential? And you need processes, but have we been too heavy-handed in some processes, and when do you need these processes?
So, I'll share with you a prediction that I'm noodling. If you look at, we've had dataops, ML ops…Do we not need to have some analytics ops or engineering ops? And there's concepts coming from somewhat the DBT community, but it's the rise of, instead of just the analyst, is it the analytics engineer? And so, it's applying some of these engineering principles to the workflow to make sure that it is scalable and repeatable. So, I still say, give the agility, maybe you need some engineering best practices applied, but at what point.
It was only 25 years ago that one of my bosses at Dow Chemical put out an edict. At that time, the way of communication was telexes. Manager would write it on a piece of paper, hand it belgium whatsapp number data over to a secretary who would put it in the telex machine that would print in some room. And you distributed these pieces of paper. That was only 25 years ago. He came out and said, "I want everyone writing their own emails." Email was new at that point in time.
So, I think when we look at low-code and no-code taking away some of the legacy manual coding processes. Should we be so afraid? Is it more about assembling and scaling?
Juan:
Super valid point.
Tim: When you think about helping people to become data DJs, how much of this is a technology problem versus a culture or a process or a people problem?
Cindi:
Yeah. It's largely culture. So, when we do roundtables, workshops around the world with our CDOs, chief digital officers, chief digital transformation officers, or heads of analytics, 67% attribute the inability to execute on their data and analytics plans to culture. To quote a survey stat from Randy Bean's new book, “Fail Fast, Learn Faster,” 92% is that combination of culture, people, and process. So, it's a big problem.
You get frustrated and you say, "Let's go buy that shiny new toy. That'll solve everything." And yet a shiny new toy without also addressing the culture, people, process problem, risks becoming shelfware which is terrible, terrible.