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Dec 5, 2013 · 1h 7m · mad

Panel discussion // Data Driven NYC #12 // Jan 2013

Sharmila Shahani-Mulligan · 16m spoken Matt Turck · 6m spoken Justin Borgman · 6m spoken Zainab (Zeneb) · 6m spoken Dane Atkinson · 5m spoken Cathy O'Neil · 1m spoken Ted Angelis · 1m spoken Matt Kroll · 1m spoken Carter Schoenwald · 55s spoken Ben Reed · 49s spoken Tony Baer · 29s spoken
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Hosted by Matt Turck at Data Driven NYC, this panel discussion brings together data entrepreneurs and experts to discuss the evolution of big data platforms, data democratization, IT governance, and practical analytics strategies. The speakers share startup origin stories, weigh architectural trade-offs, and answer audience questions on bridging the gap between technical data engineering and business execution.

How this conversation actually went

Every chapter scored 0–10 on four independent dynamics. Hover any point for the reasoning behind the score. Matt holds 11.2% of the talking time here. How this is scored →

Matt as informed peer 2.3 Guest teaching 4.2 Guest disagreement 1.2 Matt pushing back 1.0
05100:0015:0030:0045:001:00:000:00–10:02 · Matt as informed peer 1/10 Panelist Introductions and Entrepreneurial Journeys Host Matt Turck opens the panel by inviting the guests to share their personal entrepreneurial journeys. The panelists explain their company origins in a friendly, conversational manner while the host listens and facilitates.10:02–17:15 · Matt as informed peer 3/10 Point Solutions Versus Integrated Data Platforms Matt Turck frames a clear industry question on point solutions versus integrated end-to-end data platforms. The guests elaborate on market evolution, technical trade-offs, and go-to-market strategies without conflict.17:15–27:44 · Matt as informed peer 4/10 Democratization of Big Data and Data Hygiene Matt pushes the panelists on whether democratizing big data creates internal corporate tensions and turf wars with data scientists. Zainab and the SimpleReach co-founder highlight the practical complexities of data hygiene and automated cleansing.27:44–34:55 · Matt as informed peer 3/10 Interplay Between Big Data and Small Data Matt quotes Jeff Jonas regarding the relationship between big data and small data to prompt discussion. Panelists offer lighthearted and illustrative anecdotes about statistical representation and real-world domain intuition.34:55–50:01 · Matt as informed peer 2/10 Audience Q&A: IT Conflict, Tech Stacks, and Usability Audience members ask about IT conflicts, database tech stacks, and user model misinterpretation. Matt facilitates and asks a brief follow-up regarding central data warehouse trends across Silicon Valley tech giants.50:01–1:05:39 · Matt as informed peer 1/10 Audience Q&A: Consulting Trends and the Data Scientist Role Audience Q&A continues with questions on the role of consultants and data scientists. Panelists debate title definitions and customer understanding, with Zainab offering a candid perspective on organizational alignment.0:00–10:02 · Guest teaching 3/10 Panelist Introductions and Entrepreneurial Journeys Host Matt Turck opens the panel by inviting the guests to share their personal entrepreneurial journeys. The panelists explain their company origins in a friendly, conversational manner while the host listens and facilitates.10:02–17:15 · Guest teaching 4/10 Point Solutions Versus Integrated Data Platforms Matt Turck frames a clear industry question on point solutions versus integrated end-to-end data platforms. The guests elaborate on market evolution, technical trade-offs, and go-to-market strategies without conflict.17:15–27:44 · Guest teaching 5/10 Democratization of Big Data and Data Hygiene Matt pushes the panelists on whether democratizing big data creates internal corporate tensions and turf wars with data scientists. Zainab and the SimpleReach co-founder highlight the practical complexities of data hygiene and automated cleansing.27:44–34:55 · Guest teaching 4/10 Interplay Between Big Data and Small Data Matt quotes Jeff Jonas regarding the relationship between big data and small data to prompt discussion. Panelists offer lighthearted and illustrative anecdotes about statistical representation and real-world domain intuition.34:55–50:01 · Guest teaching 4/10 Audience Q&A: IT Conflict, Tech Stacks, and Usability Audience members ask about IT conflicts, database tech stacks, and user model misinterpretation. Matt facilitates and asks a brief follow-up regarding central data warehouse trends across Silicon Valley tech giants.50:01–1:05:39 · Guest teaching 5/10 Audience Q&A: Consulting Trends and the Data Scientist Role Audience Q&A continues with questions on the role of consultants and data scientists. Panelists debate title definitions and customer understanding, with Zainab offering a candid perspective on organizational alignment.0:00–10:02 · Guest disagreement 0/10 Panelist Introductions and Entrepreneurial Journeys Host Matt Turck opens the panel by inviting the guests to share their personal entrepreneurial journeys. The panelists explain their company origins in a friendly, conversational manner while the host listens and facilitates.10:02–17:15 · Guest disagreement 1/10 Point Solutions Versus Integrated Data Platforms Matt Turck frames a clear industry question on point solutions versus integrated end-to-end data platforms. The guests elaborate on market evolution, technical trade-offs, and go-to-market strategies without conflict.17:15–27:44 · Guest disagreement 2/10 Democratization of Big Data and Data Hygiene Matt pushes the panelists on whether democratizing big data creates internal corporate tensions and turf wars with data scientists. Zainab and the SimpleReach co-founder highlight the practical complexities of data hygiene and automated cleansing.27:44–34:55 · Guest disagreement 1/10 Interplay Between Big Data and Small Data Matt quotes Jeff Jonas regarding the relationship between big data and small data to prompt discussion. Panelists offer lighthearted and illustrative anecdotes about statistical representation and real-world domain intuition.34:55–50:01 · Guest disagreement 1/10 Audience Q&A: IT Conflict, Tech Stacks, and Usability Audience members ask about IT conflicts, database tech stacks, and user model misinterpretation. Matt facilitates and asks a brief follow-up regarding central data warehouse trends across Silicon Valley tech giants.50:01–1:05:39 · Guest disagreement 2/10 Audience Q&A: Consulting Trends and the Data Scientist Role Audience Q&A continues with questions on the role of consultants and data scientists. Panelists debate title definitions and customer understanding, with Zainab offering a candid perspective on organizational alignment.0:00–10:02 · Matt pushing back 0/10 Panelist Introductions and Entrepreneurial Journeys Host Matt Turck opens the panel by inviting the guests to share their personal entrepreneurial journeys. The panelists explain their company origins in a friendly, conversational manner while the host listens and facilitates.10:02–17:15 · Matt pushing back 1/10 Point Solutions Versus Integrated Data Platforms Matt Turck frames a clear industry question on point solutions versus integrated end-to-end data platforms. The guests elaborate on market evolution, technical trade-offs, and go-to-market strategies without conflict.17:15–27:44 · Matt pushing back 3/10 Democratization of Big Data and Data Hygiene Matt pushes the panelists on whether democratizing big data creates internal corporate tensions and turf wars with data scientists. Zainab and the SimpleReach co-founder highlight the practical complexities of data hygiene and automated cleansing.27:44–34:55 · Matt pushing back 0/10 Interplay Between Big Data and Small Data Matt quotes Jeff Jonas regarding the relationship between big data and small data to prompt discussion. Panelists offer lighthearted and illustrative anecdotes about statistical representation and real-world domain intuition.34:55–50:01 · Matt pushing back 2/10 Audience Q&A: IT Conflict, Tech Stacks, and Usability Audience members ask about IT conflicts, database tech stacks, and user model misinterpretation. Matt facilitates and asks a brief follow-up regarding central data warehouse trends across Silicon Valley tech giants.50:01–1:05:39 · Matt pushing back 0/10 Audience Q&A: Consulting Trends and the Data Scientist Role Audience Q&A continues with questions on the role of consultants and data scientists. Panelists debate title definitions and customer understanding, with Zainab offering a candid perspective on organizational alignment.

speaking balance: gold is Matt, purple is the guest (3 minute bins)

0:00 · Matt 31.7% · guest 68.3%0:00 · Matt 31.7% · guest 68.3%3:00 · Matt 0% · guest 100%3:00 · Matt 0% · guest 100%6:00 · Matt 0.6% · guest 99.4%6:00 · Matt 0.6% · guest 99.4%9:00 · Matt 36.3% · guest 63.7%9:00 · Matt 36.3% · guest 63.7%12:00 · Matt 0% · guest 100%12:00 · Matt 0% · guest 100%15:00 · Matt 25.3% · guest 74.7%15:00 · Matt 25.3% · guest 74.7%18:00 · Matt 11.6% · guest 88.4%18:00 · Matt 11.6% · guest 88.4%21:00 · Matt 0% · guest 100%21:00 · Matt 0% · guest 100%24:00 · Matt 24.1% · guest 75.9%24:00 · Matt 24.1% · guest 75.9%27:00 · Matt 52.2% · guest 47.8%27:00 · Matt 52.2% · guest 47.8%30:00 · Matt 0% · guest 100%30:00 · Matt 0% · guest 100%33:00 · Matt 6.6% · guest 93.4%33:00 · Matt 6.6% · guest 93.4%36:00 · Matt 0% · guest 100%36:00 · Matt 0% · guest 100%39:00 · Matt 9.4% · guest 90.6%39:00 · Matt 9.4% · guest 90.6%42:00 · Matt 0% · guest 100%42:00 · Matt 0% · guest 100%45:00 · Matt 0% · guest 100%45:00 · Matt 0% · guest 100%48:00 · Matt 0% · guest 100%48:00 · Matt 0% · guest 100%51:00 · Matt 0% · guest 100%51:00 · Matt 0% · guest 100%54:00 · Matt 0% · guest 100%54:00 · Matt 0% · guest 100%57:00 · Matt 0% · guest 100%57:00 · Matt 0% · guest 100%1:00:00 · Matt 9.9% · guest 90.1%1:00:00 · Matt 9.9% · guest 90.1%1:03:00 · Matt 11.2% · guest 88.8%1:03:00 · Matt 11.2% · guest 88.8%1:06:00 · Matt 100% · guest 0%1:06:00 · Matt 100% · guest 0%
Sharpest disagreement ▶ 54:06 Zainab's blunt critique on relying on consultants

Zainab humorously and directly states that if a company needs a consultant because they do not understand their customer, they should probably choose a different industry.

 Hardest push from Matt ▶ 24:10 Matt challenges the ideal of seamless big data democratization

Matt refuses to accept a purely smooth narrative about data democratization, pointing out that specialized data scientists will naturally defend their turf when tools automate 80% of their work.

 Biggest teaching moment ▶ 24:43 Zainab and SimpleReach explain the reality of data hygiene

Zainab turns the question back onto the panel and host regarding how data cleaning could ever be automated, illustrating how nuanced and case-by-case data hygiene really is.

 Matt holds his own ▶ 27:44 Matt frames a discussion using Jeff Jonas's industry insight

Matt displays clear industry familiarity by citing IBM luminary Jeff Jonas on how big data methodologies get repurposed for small data, forcing the panel to address the convergence of both realms.
the scores for every segment, with the reasoning behind each
ChapterTopicMatt as informed peerGuest teachingGuest disagreementMatt pushing backWhy
Panelist Introductions and Entrepreneurial Journeys 1300 Host Matt Turck opens the panel by inviting the guests to share their personal entrepreneurial journeys. The panelists explain their company origins in a friendly, conversational manner while the host listens and facilitates.
Point Solutions Versus Integrated Data Platforms 3411 Matt Turck frames a clear industry question on point solutions versus integrated end-to-end data platforms. The guests elaborate on market evolution, technical trade-offs, and go-to-market strategies without conflict.
Democratization of Big Data and Data Hygiene 4523 Matt pushes the panelists on whether democratizing big data creates internal corporate tensions and turf wars with data scientists. Zainab and the SimpleReach co-founder highlight the practical complexities of data hygiene and automated cleansing.
Interplay Between Big Data and Small Data 3410 Matt quotes Jeff Jonas regarding the relationship between big data and small data to prompt discussion. Panelists offer lighthearted and illustrative anecdotes about statistical representation and real-world domain intuition.
Audience Q&A: IT Conflict, Tech Stacks, and Usability 2412 Audience members ask about IT conflicts, database tech stacks, and user model misinterpretation. Matt facilitates and asks a brief follow-up regarding central data warehouse trends across Silicon Valley tech giants.
Audience Q&A: Consulting Trends and the Data Scientist Role 1520 Audience Q&A continues with questions on the role of consultants and data scientists. Panelists debate title definitions and customer understanding, with Zainab offering a candid perspective on organizational alignment.

Statements from this episode (12)

Prediction Not checkable as stated
Borgman: Database market will see convergence of relational tech and Hadoop
“This is where the market's going. There's going to be this convergence of, you know, sort of relational database technology and Hadoop, and this is the future, and”
Justin Borgman Dec 5, 2013 ▶ 1:46
Prediction Not checkable as stated
Dane Atkinson: Social media analytics will become as monstrous as search
“Social is the next search. This industry is going to be monstrous.”
Dane Atkinson Dec 5, 2013 ▶ 2:51
Disclosure
Justin Borgman: Hadapt commands higher selling prices targeting IT with infrastructure
“We can charge higher prices. Our average selling price is probably a lot more but we're gonna sell, you know, fewer of them, and it's gonna be to, you know, more specialized audience”
Justin Borgman Dec 5, 2013 ▶ 16:57
Assertion Not checkable as stated
Dane Atkinson: SumAll reached 20,000 active businesses and 70,000 customers
“We have, ah, we have, I guess, 20,000 active businesses, and there's about 70,000 active customers”
Dane Atkinson Dec 5, 2013 ▶ 20:19
Assertion Not checkable as stated
Dane Atkinson: Top global companies use SumAll because enterprise tools fail
“Because the tools are so weak, we find giant companies Top 10 companies putting our tools on just so they can see the social landscape in one shot, right?”
Dane Atkinson Dec 5, 2013 ▶ 20:42
Prediction Not checkable as stated
Zainab predicts a cultural movement towards broad mathematical and data literacy
“I think in general, there's gonna be a growing movement towards people being more mathematically literate in the same way that literacy had a big push before.”
Zainab (Zeneb) Dec 5, 2013 ▶ 23:18
Assertion Not checkable as stated
Small businesses radically shift marketing budgets after seeing customer retention metrics
“When we show customers what their old and new customer equation is, it's shocking how small businesses have no clue, and as soon as they see that, all of a sudden their marketing budgets get split in half, right? They start spending money for new acquisitions,…”
Dane Atkinson Dec 5, 2013 ▶ 30:12
Assertion Supported
Justin Borgman: Sears is making massive Hadoop investments to consolidate data
“Sears actually, there's been some interesting things written about Sears going in that direction. Which you think of, you know, major retail, you wouldn't think they would be, you know, compared to Facebook, but they are, and they're making huge investments in…”
Justin Borgman Dec 5, 2013 ▶ 40:53
Prediction Not checkable as stated
Justin Borgman: Big data IT consulting will decline as software matures
“I think on the IT side, ah, I think there's a lot of opportunity for consulting right now because these technologies are so new and so complicated and so hard to use, but I think, ah, as time goes on, companies like HADAP, which are really trying to productize…”
Justin Borgman Dec 5, 2013 ▶ 52:14
Assertion Not checkable as stated
Justin Borgman: MongoDB is built for web applications, not data analytics
“MongoDB, for example, is purely complementary to what we do. You wouldn't use Mongo for analytics, really, and you wouldn't use us for, You know, keeping your webpage running, for example.”
Justin Borgman Dec 5, 2013 ▶ 56:35
Insight
Cathy O'Neil: Data scientists must reject roles that treat them as implementers
“When mathematicians ask me how do you become a data scientist, I give them a lot of advice, but one piece of advice I have is if you interview with a business who thinks that you're an implementer and not a business person, then don't take that job.”
Cathy O'Neil Dec 5, 2013 ▶ 58:18
Prediction Not checkable as stated
Dane Atkinson: Companies will demand data backgrounds when hiring business roles
“So I think that, that, that, that term is going to blend, and you're going to look for people who have a data background when you're hiring for a business role, and right now it's just a, it's a titling issue.”
Dane Atkinson Dec 5, 2013 ▶ 1:04:08
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