Nov 1, 2020 · 37m · mad
Fireside Chat: Ashley Kramer (CMO & CPO, Sisense) with Matt Turck (Partner, FirstMark)
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gold bands on the timeline = statements, start to end. Hover to read, click to jump. CC turns on captions
In this Data Driven NYC fireside chat hosted by FirstMark's Matt Turck, Sisense CPO and CMO Ashley Kramer discusses the evolution of Business Intelligence platforms, cloud architecture, enterprise data democratization, and dual executive leadership in the technology industry.
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 25.8% of the talking time here. How this is scored →
Matt as informed peer 3.8 Guest teaching 3.5 Guest disagreement 0.4 Matt pushing back 0.9
speaking balance: gold is Matt, purple is the guest (3 minute bins)
Sharpest disagreement ▶ 7:15 Ashley points out missed Sisense-Periscope merger
Ashley directly flags an oversight in the host's market summary by stating 'One that you missed was Periscope and Sisense' to shift the focus to her company's deal.
Hardest push from Matt ▶ 4:39 Matt proposes strict BI vs Data Science boundaryMatt tests the guest's definition by offering a detailed reframe distinguishing historical descriptive BI from predictive data science.
Biggest teaching moment ▶ 7:15 Ashley educates host on Periscope SQL dynamicsAshley corrects the host's oversight regarding BI consolidation and explains how merging code-based SQL analytics with drag-and-drop UI solves organizational tooling redundancy.
Matt holds his own ▶ 10:57 Matt accurately maps Sisense onto the modern data stackMatt demonstrates deep sector knowledge by accurately paraphrasing the roles of ElastiCube, cloud warehouses (Redshift, BigQuery, Snowflake), and ingestion engines like Fivetran.
the scores for every segment, with the reasoning behind each
| Chapter | Topic | Matt as informed peer | Guest teaching | Guest disagreement | Matt pushing back | Why |
|---|---|---|---|---|---|---|
| Ashley Kramer's Professional Background and Career Journey | 1 | 3 | 0 | 0 | Matt asks a light biographical question about Ashley's NASA beginnings. Ashley provides a detailed history of her career transitions through Oracle, Amazon, Tableau, Alteryx, and Sisense. | |
| Defining Modern Business Intelligence and Predictive Analytics | 4 | 4 | 1 | 2 | Matt attempts to frame the historical distinction between BI and data science. Ashley validates his view while reframing how Sisense embeds algorithms to close the skillset gap. | |
| BI Market Consolidation and the Sisense-Periscope Merger | 5 | 5 | 2 | 1 | Matt demonstrates high industry awareness by listing acquisitions like Tableau/Salesforce and Looker/Google. Ashley politely points out that Matt missed Sisense's own major merger with Periscope Data. | |
| Sisense Platform Architecture and Data Warehouse Integration | 6 | 3 | 0 | 2 | Matt shows strong technical familiarity with the modern data stack, citing Fivetran, Snowflake, BigQuery, and Redshift while accurately paraphrasing ElastiCube's architecture. | |
| Leveraging Local and Universal Knowledge Graphs for Insights | 5 | 4 | 0 | 1 | Ashley explains local versus universal knowledge graphs using a Netflix analogy. Matt synthesizes the point by highlighting the underlying data network effect. | |
| Moving Beyond Dashboards with Embedded Analytics Workflows | 5 | 2 | 0 | 1 | Matt cites a specific metric noting that embedded white-label analytics accounts for roughly 50% of Sisense's business, which Ashley confirms and contextualizes. | |
| Democratizing Enterprise Data and AI-Driven Data Preparation | 5 | 3 | 1 | 2 | Matt challenges standard BI adoption metrics by pointing out the typical bottleneck of central analyst queues. Ashley elaborates on moving toward proactive insight delivery. | |
| Identifying Core User Personas and Developer Portal Workflows | 3 | 4 | 0 | 0 | Matt asks how product leadership handles multiple personas. Ashley breaks down the taxonomy of data teams, BI managers, and external product builders. | |
| Future Product Roadmap and Decision Automation AI Innovation | 3 | 3 | 0 | 0 | Matt brings up Sisense's recent unicorn valuation and $100M funding round, prompting Ashley to outline the product vision for decision automation. | |
| Aligning Product and Marketing in a Dual CPO/CMO Role | 4 | 3 | 0 | 1 | Matt probes the unusual combination of dual CPO and CMO roles and asks about executive diversity. Ashley explains her leadership structure and thoughts on STEM pipelines. | |
| Audience Q&A: Industry Vertical Solutions and Customer Success | 1 | 4 | 0 | 0 | Jack reads audience Q&A questions regarding industry verticals, market positioning, and ROI. Ashley provides structured responses outlining Wave 3 analytics. |
Statements from this episode (14)
Sisense considers its major acquisition of Periscope Data to be a merger
“So Sisense made an acquisition in of Periscope data. It was a big one. So we actually consider it a merger.”
Sisense re-architected its analytics platform on microservices for cloud scaling
“We're completely microservices based architecture. Another decision made to stay ahead of the game was a rewrite of the platform. And so now we can fit into any cloud ecosystem in scale as the data and the analytics scale.”
Sisense added data pipeline capabilities for direct write-backs to cloud warehouses
“The new capabilities that we've added is being able to write back to the cloud data warehouse.”
Sisense's knowledge graph leverages 650 billion metadata points collected over ten years
“What the universal knowledge graph does, the second piece is it takes six hundred and fifty billion data points collected over the past 10 years, again, metadata points, and it's able to provide knowledge out of the box.”
Traditional BI dashboards drive low adoption by interrupting user workflows
“What we see our customers asking for and where we see the market going is People want the analytics to come to them. They don't want to stop what they're doing and go look at a dashboard and come back to what they're doing. That's why we're seeing a low adopti…”
Embedded analytics accounts for roughly half of Sisense's overall business
“So from the OEM white labeled side, so being embedded in other products it's about half of the business”
Over 400,000 data analyst jobs are currently posted online
“There's over 400,000 data analysts jobs posted.”
Data literacy will not improve quickly across enterprise organizations
“Data literacy is not going to solve itself quickly. And we're not going to see this explosion of trained analysts.”
UiPath uses Sisense to power its RPA analytics and monitoring
“UiPath is a public one that we do that with. So when you're using UiPath's RPA, all of the monitoring and all of the analytics within is Sisense.”
Sisense plans to integrate Python and R into a notebook interface
“Coming soon, we will also integrate the rest of the notebook like experience, being able to put Python and R within the experience and instantly get your insights.”
Siloing product engineering from marketing and sales creates messaging gaps
“You generally see product and engineering as great partners and marketing and sales as great partners. And that always leaves a gap between what's happening in product and how are we messaging it?”
Kramer: Marketing and HR have more female leaders than technical roles
“We do tend to see more of the marketing and the HR functions still have the greater amount of women leaders versus some of the more technical.”
An airport cart client achieved 400 percent ROI within three months
“So we had a customer, That was able to work with us and within three months because of how they were able to optimize their inventory. They do carts within airports. So this was obviously before COVID. They were seeing a 400% return on investment.”