Dreamforce was everything I hoped for and more! Epic week meeting new friends, peeking into the future of ai agents, learning and laughing in the California sunshine.
Loved running into fellow #datafam@tableau folks in a sea of Trailblazers!
@salesforce#DF24#dreamforce
Dreamforce highlight of the week was spotting California governor @GavinNewsom cruising the Campground expo hall. Love the support, and grateful to share a few kind words with such an influential leader. ππΌππΌ
@salesforce@tableau#datafam
Denver @myfirstmilpod meetup:
More than networking, this group has been an amazing place to meet other founders to:
- Generate new ideas
- Encourage each other
- Challenge assumptions
- Keep each other accountable
And the birth place of @HavenFounders π€πΌ
@thesamparr@ShaanVP
Yo Denver #datafam β Join us for our very first edition of the **Denver Data Lunch Crew** on Thursday, June 27th. We're meeting at @zeppelinstation and it's bound to be a good time!
Brought to you by your very own Denver @Tableau and @Alteryx user groups.
@chaseadams Saw this and thought wow that looks a lot like my stairs built by Classic Homes in Colorado Springs. Dude do you live in Flying Horse too???
Officially ready for @tableau conference #Data24 with some fresh biz cards. π€Looking forward to making some new #datafam friends and reconnecting with old ones! San Diego, here we come!
@hoytcrouch Iβm working on a feeder for Hampton. Exact same model, but for six figure founder/CEOs looking to scale to $1M+ and graduate up to Hampton. Weβre forming initial groups now. If youβre interested in applying, hit me up!
People often ask what skillsets are needed to be successful in #DataAnalytics . I've been brewing on this model for almost a decade, and it's time to share.
World class #data#analytics professionals are strong in three areas: business acumen, technical expertise, and design skills.
Let's take a quick look at each:
β BUSINESS
What should we build for the end user? Why do they need that insight? When do they need it? What levers can they now pull because they have it? Which metrics actually matter to the business?
β TECHNICAL
How do we build it? Can we click the right buttons, drag the pills, configure the report, write correct SQL statements and calculations? How do we construct the pipelines and perform the integration/preparation? How should we architect the data warehouse/lake/lakehouse? Which tools should we use?
β DESIGN
How do we delight our users by making the tools pretty and easy to use? Do we use visual best practices, select the right chart types, use color appropriately? Can users quickly understand the tool and easily navigate it?
Three legs of the same stool. Without one, the whole thing falls over. More to come on that. ;)
What would you add?
Where does data storytelling fit in?
People seem to be fretting over AI stealing jobs from knowledge workers.
Specifically in the data analytics world, it seems many mid-market companies are kicking their proverbial "data can" down the road in hopes that someday AI will solve all of their data challenges.
But even once the tech is there, the most important question is not if AI can build you a data warehouse and some dashboards. Sure, it will be able to.
To borrow/adapt from my buddy Mark here...
It doesn't matter if AI automates the tactical side of standing up a data stack.
Our most valuable role as data practitioners has always been figuring out what should be built in the first place.
I just told ChatGPT to write a lot of code and then walked away to pet my dogs, only to come back to the correct result. Yeah, we're living in the future.
It really doesn't matter if AI automates most of writing code. The most important thing has always been figuring out what code should be written!