Issue #1 - We Need to Rethink Data

Our industry is too confusing for its own good

Read time: 5 minutes

Intro

Welcome to my newsletter.

It’s a long time coming. Actually, a lot of people thought I already had a newsletter about Bridging the Data and Strategy gap.

But data strategy is not a new thing and there are so many experts out there already talking about it.

So me, being probably overly ambitious, decided to take a different angle/ approach. Let’s put a magnifying glass on not one data subject, but all of them. Let’s simplify the complexity that is the whole data industry, one 5-6 minute newsletter article at a time.

Okay So What’s the Problem in Data?

If you traverse Data LinkedIn for even ten minutes, you find a continuously growing list of problems in the data field:

• Poor data quality

• Integrating data sources

• Lack of leadership support

• High costs of talent and tools

• Unrealistic requests and timelines

• Not thinking with a business mindset

• Poor data quality again

None of these issues are a surprise for any data professional out there, and we as an industry absolutely LOVE complaining about them. And research backs up these statements, citing data quality, buy-in, poor systems, and access as top challenges companies are facing in today’s data world.

LNS Research

But beyond all this, one must remember there is a difference between symptoms and root causes. Symptoms are outward manifestations of issues—the signals our bodies or circumstances give, often capturing immediate attention. Root causes, however, are the underlying factors, the bedrock upon which symptoms emerge, often concealed beneath layers of complexity.

Data professionals—in our quest for quick resolutions—frequently mistake symptoms for root causes.

Therefore, the surface issues are addressed while the foundational problems persist. And executives who don’t know anything about data are even worse at this (and why this newsletter is aimed at them as well, so tell your boss about it if they want to learn the ‘so what’ about data)!

As an industry, we are getting better at this. But work still needs to be done, because so many issues exist across the data world, and a lot of it is due to a lack of understanding or a common language that brings data and non-data professionals together.

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The Data Ecosystem – One Topic That Hasn’t Been Covered in Data

Introducing The Data Ecosystem

Data isn't easy. It's incredibly complex. What is worse though, is nobody appreciates how complex it is. And nobody has really tried to solve it. Instead, people keep moving on to the next thing.

I officially dub this “The sexiest philosophy question of the century”

Here's the reality: 𝐭𝐡𝐞 𝐝𝐚𝐭𝐚 𝐢𝐧𝐝𝐮𝐬𝐭𝐫𝐲 𝐢𝐬 𝐧𝐨𝐭 𝐚 𝐜𝐨𝐥𝐥𝐞𝐜𝐭𝐢𝐨𝐧 𝐨𝐟 𝐢𝐬𝐨𝐥𝐚𝐭𝐞𝐝 𝐟𝐢𝐞𝐥𝐝𝐬; 𝐢𝐭'𝐬 𝐚 𝐜𝐨𝐦𝐩𝐥𝐞𝐱, 𝐞𝐯𝐨𝐥𝐯𝐢𝐧𝐠 𝐞𝐜𝐨𝐬𝐲𝐬𝐭𝐞𝐦. How can we innovate, how can we truly advance, if we don't understand how these pieces fit together? This siloed approach isn’t just inefficient; it's a roadblock to progress.

Let’s briefly explain:

In the data industry, it’s easy to become entangled in the minutiae of singular domains, much like the saying goes how people fixate on individual trees and not seeing the forest. Data thrives on the interconnectedness of its domains and to truly grasp the essence and potential of the data industry, one must ascend above the tree line.

From this vantage point, the forest reveals itself not as a collection of isolated entities, but as a dynamic ecosystem where each domain contributes to and is influenced by the whole. Understanding the data industry in its entirety allows for the identification of overarching patterns, trends, and opportunities that remain obscured at the ground level. It's a reminder that while specialization has its merits, the power of perspective in weaving together a comprehensive understanding cannot be underestimated.

Am I Credible Enough to Explain This All?

In short, probably not. I’ve never built a data pipeline, I last opened RStudio 2.5 years ago, I still can barely explain what Databricks and Snowflake even do, and I am highly sceptical when companies try to build AI tools.

But maybe all those reasons are exactly why I’m the right person.

My niche is about bridging that gap (like below).

I’ve been trained to take complex ideas and articulate how they fit together. I’ve worked a decade in strategy consulting and have helped dozens of billion-dollar companies figure out how to approach data (and navigate their own ecosystem). Throw in my decade of R experience (building websites and apps in R) to my love of learning and researching everything about an industry that continues to get more confusing by the day. If you haven’t read my stuff, pop over to my LinkedIn page and follow along.

So What Are You Getting as the Reader?

To succeed in this venture will require thinking beyond the box and connecting the dots. It is about absorbing expertise from domain leaders, and pushing publish with an expectation that you may have missed something. Most importantly, it is about distilling lots and lots of information into something that matters and will make an impact.

And with that, I aim to arm each reader with the elevator pitch for every part of the data ecosystem and why it matters.

With this newsletter I am to pull all of this together. Leveraging the amazing work each expert has done, The Data Ecosystem will articulate the ‘so what’ for each data domain. This includes:

• What it is?

• Why it matters?

• Its impact on the business

• Some cool/ essential frameworks to illustrate key concepts

Treat this newsletter as the CliffsNotes or the for Dummies of the entire Data Industry, succinctly articulated in a weekly thought piece. And hey, if I’ve missed something or need to update some ideas, please comment below and hit me up!

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Thanks for the read! Comment below and share the newsletter/ issue if you think it is relevant! Feel free to also follow me on LinkedIn (very active) or Medium (not so active). See you amazing folks next week!