Zeer Dataiku / intent / dataiku
Observed, not inferred · updated weekly

Dataiku buying intent

21 tracked signals — top 15 topics below — Data and Sales are carrying most of it.

21signals · 30 days
15topics tracked
16.67%attributed to a team

Attention by team

taxonomy_intent_rollup × social_profile.role

Every tracked signal from a Dataiku employee, placed by the team they sit in and the theme they engaged with. Darker means more concentrated attention.

Artificial Intelligence
Azure Databricks
Confluent
Data Lakehouse
Data Science
Data Warehouse
Data
1100% Data to Artificial Intelligence: 1 signals, 100% of this team's attention
00% Data to Azure Databricks: 0 signals, 0% of this team's attention
00% Data to Confluent: 0 signals, 0% of this team's attention
00% Data to Data Lakehouse: 0 signals, 0% of this team's attention
00% Data to Data Science: 0 signals, 0% of this team's attention
00% Data to Data Warehouse: 0 signals, 0% of this team's attention
Sales
00% Sales to Artificial Intelligence: 0 signals, 0% of this team's attention
00% Sales to Azure Databricks: 0 signals, 0% of this team's attention
1100% Sales to Confluent: 1 signals, 100% of this team's attention
00% Sales to Data Lakehouse: 0 signals, 0% of this team's attention
00% Sales to Data Science: 0 signals, 0% of this team's attention
00% Sales to Data Warehouse: 0 signals, 0% of this team's attention
Unclassified no dept on file
660% Unclassified to Artificial Intelligence: 6 signals, 60% of this team's attention
110% Unclassified to Azure Databricks: 1 signals, 10% of this team's attention
00% Unclassified to Confluent: 0 signals, 0% of this team's attention
110% Unclassified to Data Lakehouse: 1 signals, 10% of this team's attention
110% Unclassified to Data Science: 1 signals, 10% of this team's attention
110% Unclassified to Data Warehouse: 1 signals, 10% of this team's attention
LowHigh

Topics being researched

30-day window

All tracked topics, ranked by signal volume. Confidence is the classifier's certainty that the signal belongs to this topic.

Artificial Intelligence
LinkedIn
High volume
98%
last
3d ago
Azure Databricks
LinkedIn
Low volume
98%
last
29d ago
Confluent
LinkedIn
Low volume
90%
last
28d ago
Data Lakehouse
LinkedIn
Low volume
98%
last
29d ago
Data Science
LinkedIn
Low volume
98%
last
29d ago
Data Warehouse
LinkedIn
Low volume
98%
last
29d ago
Employee Engagement
LinkedIn
Low volume
50%
last
28d ago
Employee Voice
LinkedIn
Low volume
65%
last
28d ago
Global Procurement
LinkedIn
Low volume
98%
last
26d ago
Machine Learning
LinkedIn
Low volume
98%
last
29d ago
Machine Learning Ops
LinkedIn
Low volume
98%
last
29d ago
Paw Partner
LinkedIn
Low volume
55%
last
26d ago
Snowflake
LinkedIn
Low volume
98%
last
29d ago
Agentic AI System
LinkedIn
Low volume
98%
last
21d ago
Strategic Sourcing
LinkedIn
Low volume
98%
last
26d ago

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Who to contact at Dataiku

verified title on file

People at Dataiku whose own activity produced these signals. Names are withheld pending a consent decision; titles, seniority and topic are real and free to browse.

Sales2 active
Sales Engineer
researching Confluent
in
Business Development Representative
researching Paw Partner
in
Unclassified1 active
Country Manager, Japan
seniorresearching Data Science
in
CEO at Dataiku
executiveresearching Artificial Intelligence
in
Regional Vice President
researching Machine Learning Ops
in
UX Designer I
researching Employee Engagement
in
Field Chief Data Officer, APJ
executiveresearching Artificial Intelligence
in
Data1 active
Data Scientist
entryresearching Agentic AI System
in

Top accounts researching Dataiku

names withheld on the public page

Companies whose people mention Dataiku in their own activity. Account names are withheld here; not yet classified as implementation partner vs. genuine prospective buyer.

Not yet available

No buyer signal yet for this account

Nobody in the graph is currently discussing this company by name in a way we can attribute to a specific employer.

Buyer profile

company size · seniority

How big those accounts are, and who inside them is senior enough to matter. Competitor products still not yet computed for this account.

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Company-size breakdown and buyer seniority mix for accounts researching Dataiku.

Company size breakdown
Buyer seniority mix
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Not yet available

No buyer signal yet for this account

Not enough real data was found to build a company-size or seniority breakdown for this account.

What's been said

public posts mentioning Dataiku

Real public activity that surfaced Dataiku in a tracked topic. Not a sentiment score — just what people actually wrote.

LinkedInArtificial Intelligence

These days, when I say "agent," I say it in ✌🏻quotes✌🏻. Not to be contrarian, but because the word feels transient and ill-defined, and I keep coming back to that at events like HumanX last week. Transient in etymology. "Agent" is a placeholder borrowed for an enormously wide category of software capabilities. "Website" was a word like that in 1992, technically accurate, practically useless. What actually transformed industries were blog, e-commerce, social media, landing page. The generic term was just the scaffolding. The specific forms were the revolution. "Agent" is boring. What comes after it won't be. Ill-defined in implementation. From a technical standpoint, an agent is an LLM-based loop with state and tools that give it some degree of autonomy. Fine. But that definition buries the real thing happening: you're replacing a human interacting with software... with a piece of software that is not fully deterministic. The intrinsic value is human replacement for that task. The intrinsic risk is the X : the unknown behavior of a non-deterministic system acting in the world. We're essentially substituting something kind of predictable (a person following a process) with something probabilistic (a model making calls). Which one is easier to control is a longer discussion - but that's a profound shift, and beyond its current implementation, that's what AI really is. I'm not sure "agent" carries the weight of it. So yes, ✌🏻agents✌🏻 For now. Thanks Gautier Cloix and Sabrina Ortiz for the convo Thanks Stefan Weitz for the great event.

Apr 2026
LinkedInAzure Databricks

AI Days is bringing the data and AI community together across cities around the world! Practitioners joined us for hands-on sessions, technical deep dives, and demos showing how teams are building AI applications on the Databricks Data Intelligence Platform. Across each stop, attendees explore how to: • Build and deploy AI agents with Agent Bricks • Power applications with Lakebase Postgres • Unlock insights using natural language with Genie Thank you to our speakers, partners, and everyone who joined us to learn and connect. More cities are on the way. Find the next AI Days near you: https://lnkd.in/e8ikDZR8

Apr 2026
YouTubedeployment / implementation time

Taking a decision is one hour. Putting it in place is like two years.

About this data. Dataiku (dataiku.com). Signals derive from taxonomy_intent_rollup joined to social_profile.role. Department attribution is 16.67%; the remainder is shown honestly as its own Unclassified row rather than hidden. Updated 2026-08-24T04:00:02.375Z.

Not yet computedPer-team narrative summaries