WTF is Data Engineering? (video)
WTF is data engineering? Good question. Here’s a presentation I did this week for AI Startups SF, where I described what data engineering is, what data engineers do, myths, and the future of data engineering. Enjoy!
Data
What is a recovering data scientist?
“What is a recovering data scientist?” This question arrives in my LinkedIn messages at least once a week. It’s easy to see why, since my LinkedIn title says “recovering data scientist”. While “recovering data scientist” is admittedly a bit clickbaity, there’s also considerable truth to the moniker. The “recovering data scientist” schtick started several years … [Read more…]
The Path Of A Reluctant Data Scientist
I’m a self-described “reluctant data scientist”. Wait? Didn’t Harvard say that data scientist is the hottest job of the 21st century? Why would someone reluctantly claim title to the rockstar status, money, and glory that come along with being a data scientist? In my personal experience, there’s a big gap between data science hype and the … [Read more…]
The Point Of Struggle – Ai vs Balkanized Reality (Podcast)
In this episode of The Point Of Struggle, David Gonzalez and I riff on AI, ethics, and balkanized reality. Listen here The conversation ties to a post I wrote in March about leaving Facebook. Expect more conversations like this, since its a topic that I constantly think about. Speaking of which, a tweet this morning … [Read more…]
Unfriending Facebook, AKA Derpbook
After over a decade on Facebook, I finally decided to unfriend Facebook. The recent revelations of Facebook’s latest fiasco with Cambridge Analytica (and likely hundreds or thousands of similar incidents) was the tipping point for me. Actions. Not words. Enough is enough. #deletefacebook pic.twitter.com/EaCnzlOWID — Joe Reis (@josephreis) March 21, 2018 For the last couple … [Read more…]
Podcast on The Point Of Struggle – AI – Paying for your sins and creating a productive data-driven culture
“How much effort are you willing to put in to correcting your past sins and atoning for those before you move up the sophistication ladder. I would argue it would be a good practice to do especially if you’re going to start marrying your business data with any unstructured data that you’re going to be … [Read more…]
The AI Hype Cycle, Talent Wars, And Internet Comment Threads
Last week, somebody on Hacker News posted a link to a Bloomberg article titled “Sky-High Salaries Are the Weapons in the AI Talent War”. The article itself was good, and predictably discussed how the shortage of AI talent is driving up salaries. But what really stood out for me were the Hacker News comments on … [Read more…]
Use The Source – A Quick Tip For Re-Architecting With Legacy Data
One of my client engagements involves re-architecting the data and BI platforms for an 80 year old company. As you can imagine, there’s a ton of data across countless legacy systems. Data and systems have piled on top of each other over the decades. The vast majority of the data is undocumented, derived (hence, possibly … [Read more…]
Your Company Probably Isn’t Ready For Data Science (And That’s OK!)
Your company wants to “do data science” ** or “become a data company”. These are definitely noble and well intentioned goals. Not trying to be negative, but I’m going to bet that your company probably isn’t ready for data science. And that’s perfectly OK. For the past several years, I’ve led data initiatives for companies … [Read more…]
SLC Python Talk – Code and Presentation Link
On Wednesday, 12/6/2017, I gave a talk at SLC Python to a standing room only audience. This was a record setting attendance for the SLC Python meetup. Apparently time series forecasting is a popular topic 😉 Here are the materials from my talk, posted on GitHub.