Ok, I’m still working on the name, but as I’m ramping up my practice and engaging in conversations, I felt compelled to do some digging to quantify where attention and momentum actually are in the D&A space.
Once a data analyst, always a data analyst.
I started with a list of 63 terms (already an opportunity for debate) and ran them through Google Trends, normalizing on an anchor and indexing everything on a 0-100 scale. I identified direction by comparing trailing averages, along with some very basic seasonal adjustment, and a dash of qualitative sauce based on funding announcements, press releases, LinkedIn, and Reddit.
Side note: StackOverflow, we hardly knew ye…
This is far from perfect and notably doesn’t measure the relative importance of a term. Mature categories may score lower and be stable, but remain critical. Data pipelines aren’t going anywhere, but they’re also not what people are buzzing about.
The Findings
- Data quality tops the index: I love this result! This is the get-your-hands- work I’ve been doing since day one, now entirely reimagined in the age of observability.
- AI agents (99) is massive: No surprise here. The term has full mainstream traction and has saturated our awareness.
- Data products (72) is the highest-volume rising term. The data-as-a-product movement is gaining real traction, and Data governance (38) is also rising. The governance stack is having a (personally heart-warming) moment.
- Infrastructure categories are declining. Data lake (49), Lakehouse (34), Delta Lake (27) are all declining. Again, these aren't failing, but graduating from "emerging" to "assumed."
- Data observability (4) is rising, but from a low base. This one surprised me, but it’s also niche terminology. RAG (7) has the same problem…the category is real, vendors are consolidating, practitioners care, but mainstream search interest is nascent.
The Leaders
Here are the terms that topped the list:
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
What's Rising
26 terms are showing upward momentum, including:
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
The rising terms cluster around two themes: governance and productization, and operational maturity. The market is shifting from "build the stack" to "run the stack reliably."
What's Declining
23 terms are declining in search prevalence (reminder: declining means less searched, not less important), including:
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
Data fabric and data mesh are both showing declining interest after periods of heavy attention. Vector database and fine-tuning are also cooling as the AI hype cycle corrects. Terms that dominated discussions two years ago are now normalizing.
Implications for the Industry
- Quality and Observability dominate the discussions: It’s back to basics. Every AI initiative, governance program, or analytics modernization eventually hits the same wall…the data isn’t ready.
- The governance stack is where the action is: Data products, data governance, data risk management, data stewardship…all rising. If you're building or buying, this is where practitioner attention is heading.
- Infrastructure is a given: Data lake, lakehouse, streaming: still high volume but declining interest. These aren't going away, they’re just assumed.
- Watch the AI over-hype: Vector database, fine-tuning, MLOps: all declining. This doesn't mean AI is failing, as much as over-promising. The winners will be the tools that deliver on the promises.
The Trend-splainer Going Forward
This was a fun exercise, but the methodology has holes. If you have ideas, challenges, or are interested in the full list, find me on LinkedIn.
If this proves fun or engaging for others, maybe I'll formalize it. Call it whatever you want (better name suggestions are welcome). This is just my own sanity check on the buzz in the market.
And if someone’s going to keep score, might as well be the data analyst.
Comments ( 0 )