Ready To Growby Jay Cuthrell
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First, you might recall my shot and chaser format from prior issues. Essentially, I call back to a prior reference in an issue with a current link to how the prediction or topic turned out in the market.
Well…. Sometimes my shot and chaser game is freaky accurate. 😳🤣
There’s prescient and then there is prescient.
And… nailed it.😳🤣
[Twitter Write @TwitterWrite✨ Introducing: Notes ✨
We’re testing a way to write longer on Twitter. ](https://twitter.com/TwitterWrite/status/1539640956915290112)[4:06 PM ∙ Jun 22, 2022
Telecom was and arguably still is a game of titans. The game of titans for the future is cloud and seeing the crossover over into aerospace, telemetry, as well as in the new digital highway of 5G/ORAN/vRAN will be exciting.1
One theme I’ve covered in this newsletter is technologies we use to seek insights from data generated in the past, present, in the future2. As data continues to grow, our tools will evolve and entirely new disciplines will emerge that might, at first, seem like science fiction.
Since technology is the response to a perceived need, it’s not shocking that business and other organizations perceive the need to predict outcomes based on analyzing data. So, in response there is fast growing market for predictive analytics could easily approach ~$1T USD in just a decade or so.3
The use cases of predictive analytics are only bound by where tools and techniques are being applied.4 For example, the most conspicuous predictive analytics for consumers is found within sophisticated online shopping experiences where you see realtime advertising of what other customers like you also purchased – and of course – with a convenient single click option to add these recommendations to your shopping cart.5
Another theme I’ve covered is related to the growth of low code and no code tools on the horizon6. So, in the meantime, it’s probably a safe assumption that predictive analytics will be a far more accessible growing market for far more individuals than ever before as data driven applications and data first use cases widen to every aspect of business and operational processes.
My newsletter reading has expanded and I’m picking up on more podcasts as well as video content. As a result, my aperture has widened to people I’ve never worked with that are often far outside my cloud, infrastructure, and telecom past.
So, for the rooftop selection, I’ve found an interesting video podcast where I’ve learned about how others are entering predictive analytics in their career pursuits. Enjoy this YouTube channel selection from The Data Scientist Show where Daliana Liu interviews people from across the rapidly growing data science community.
I mentioned in a prior issue that I would be dropping the read and repo section of my newsletter. So, instead, I’m going to try amplifying some great content (like the above) that I’ve come across in my reading outside my 2nd and 3rd degree network (to use the LinkedIn terminology) made possible by through conscious time investments in Lunchclub.com.7
When it comes to the Interwebs, there is a lot to read. More recently, on the Interwebs, there is also a lot to listen to and a lot to watch as podcasts have reached the 2M mark.8
It’s recently occurred to me that there is an absolutely incredible amount of content vying for our attention and many of my readers are commonly faced with corporate decision making. Indeed, the same Nobel Laureate economist that drove much of what constitutes our understanding of corporate decision making also coined the term “attention economy” over half a century ago.9
And speaking of storytelling… my latest reading is Karla Starr’s Substack.10 So, if you are a sales engineer / developer advocate / data scientist / etc. giving a presentation – then you know the great power (that comes with great responsibility) of taking questions and answering with “it depends” and you’ll probably hurt your neck nodding along when reading this post:
The Starr ReportYoda would not have his own podcastYesterday I had the nerve-racking delightful experience of giving a guest lecture on how to use numbers in storytelling for Section4. Have I been kicking myself since for not going slower, using more advanced tips, etc., etc.? Have I been obsessing over what I could have done better? Do I know how useless regret is…Read more7 months ago · 12 likes · Karla StarrSo, can you change your luck? It’s a question we often wrestle with in our careers.
Well, if you liked the Substack post above, you’ll love Can You Learn to Be Lucky (CYLTBL). CYLTBL is insightful and a fun read in addition to having incredibly detailed footnotes to original sources as superb pointers for diving deeper into topical references.
Finally, this brings me to my latest decision for my newsletter and use of Substack: I’m going to end my audio podcast testing on Substack where I’m simply… reading back my Substack. As it turns out, the Substack iOS app will actually read the text of a post so my podcast was superfluous at best — and I’m not Yoda either but I digress.
After all, when my home office studio is completed with all the video accoutrement it will provide a context for referencing The Buggles.11
If you’re curious about Faction please check this links roundup of our latest media coverage from April 2022 to June 2022:
- Dataversity: The Rise of Enterprise Data Inflation
- Coruzant Digital Executive Podcast
- Authority Magazine: Agile Businesses: On How Businesses Pivot and Stay Relevant In The Face of Disruptive Technologies
- GRC Outlook: Data Security - Going Back to Basics
- InsideBIGDATA: Heard on the Street
- Dataversity: Five Ways Multi-Cloud is Accelerating Medical Science
- The Enterpriser’s Project: Moving Cloud Workloads - 4 Essential Strategies
I am linking to my disclosure.
✍️ 🤓 Edit on Github 🐙 ✍️