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by Pete Fishman
About the Speaker
Pete Fishman is the co-founder of Mozart Data. In this segment, Pete gives a short introduction about the trends in the data and solutions to data problems.
Pete prefaces the conference by sharing exciting trends in the data world, including the explosion of data volumes, the rise of data professionals and data-adjacent careers, as well as the rise of SaaS tools, including Mozart Data.
He continues by outlining why traditional methods in data solutions, including the downloading of CSV files, have become inefficient. Pete points out the following: It takes a lot of time, it’s error-prone, the data is siloed, and replication is difficult.
The right way of bringing together multiple data sources is building a data pipeline — creating a bunch of data, extracting that data to a data warehouse, and transforming and cleaning that data before using it to create reports using a data visualization tool.
That data pipeline could be tricky to build, but with the help of Mozart Data, creating your modern data stack could help you maximize the value out of your data.
by Derek Steer
About the Speaker
Derek Steer is Co-Founder and CEO of Mode, an analytics platform designed to help data analysts and data scientists analyze, visualize, and sharedata.
In our first-ever user conference, Derek talked about the history of the modern data stack, and where it could go in the future. He began with the idea that many SaaS businesses exist because of the modern data stack due to the influx of innovation.
One example Derek shared is how video game companies like Zynga adopted a strategy of combining their product activity data and purchasing data to design products for maximum revenue generation — a framework that modern B2B companies have since then copied.
Derek then highlights data innovations in the past 15 years: Big Data, The Cloud and the rise of data science.
All of these pivots have paved the way for a big shift — the commoditization of data storage and processing. Open source tools like Hadoop weren’t supported by vendors, and administering these tools became too big of a burden aside from big companies that could afford the costs. Today, startups or smaller companies could perform the same tasks in a more accessible way. To win the modern data stack, he suggests the following:
Design your data stack to be as modular as possible.
Ensure that you are tracking events for any key action, and that events are easily usable in any system that needs them.
Optimize the system, not each component.
Design with the newest advancements in mind.
by Dan Cho
About the Speaker
Here’s Dan Cho, Senior Director of Operations and Chief of Staff of Tempo, an at-home fitness software company personalizing weight training through real-time form corrections and custom workout plans.
At Tempo, data is at the very core of their base of operations. Dan, in conversation with our very own Kritika Dusad, shared Tempo’s growth during the pandemic, the data challenges they faced, and how Mozart Data addressed those challenges.
One of the big challenges Tempo faced was the rapid pace of new teams and functions. With Mozart Data, early-stage companies like Tempo could get ahead when new tools are implemented, so that they could end up where they want to be down the line.
An executive dashboard was created to show the value of having a centralized data stack. “Mozart took the burden of getting everything centralized off the plate,” according to Dan. With one click of a button, all the metrics could be seen.
“Without Mozart [Data], it would have been all spreadsheets. That would have been a nightmare,” Dan adds. Mozart Data allows for data reliability especially for a startup at their early stages wherein not all data are checked for quality assurance. Through Mozart Data, questions can be answered right off the bat.
by Shruti Gandhi
About the Speaker
Shruti Gandhi is the founder of Array Ventures, a venture capital firm investing in deep tech early stage companies. She is also the lead investor at Mozart Data. Listen to her talk about investing in data, and why Peter and Dan Silberman are the right people to tackle the problems around the modern data stack.
In conversation with Mozart Data’s data analyst Adam Pharr, Shruti shares her investor perspective on the differences in managing a tech startup before and during the COVID-19 pandemic. She outlines the need for community building.
Shruti also expounds on why she decided to invest on Mozart Data: “What Mozart Data’s working on is something I’ve been excited about for a while, but also the team. Pete [Fishman] and Dan [Silberman] know the space well…I wouldn’t say there’s any other team that knows how to solve this problem today.”
“I’m excited to back [Mozart Data], and just be part of the journey and be available as necessary as a friend or as part of an investor group of people,” she adds.
by Dan Silberman
About the Speaker
Dan Silberman is the co-founder and CTO of Mozart Data. In this talk, Dan discusses the goal of Mozart Data as well as presents a walkthrough while showing what lies ahead through a product roadmap.
For Mozart Data, the goal is to allow people who use data to do their jobs better, by being the easiest way for data professionals to get access to the benefits of working in a modern data stack. Dan presents how that goal is realized through a demo of how Mozart Data works.
According to Dan, the true power of Mozart Data comes from combining data from connectors and organizing data into usable tables. A core design principle of Mozart Data is that as long as you know SQL, you will have access to build data pipelines and organize your data. Through the transformations, you will have access to one source of truth.
At the highest level, Mozart Data helps you get data in with connectors, helps you organize, categorize, and annotate your data once it’s in your data warehouse, and finally empower the rest of the company by integrating with popular BI tools.
Another core product of Mozart Data is the above-and-beyond customer support.
Sign up for a free trial or schedule a demo. We’ll be happy to talk to you about your data journey.
by Daniel Adler
About the Speaker
Daniel Adler is the Assistant General Manager of the Minnesota Twins, a professional baseball team based in Minneapolis, Minnesota.
In this talk, Daniel discusses the different problems that affect good decision making, and how data can overcome those problems using real-life situations in the realm of sports as examples.
Daniel outlines certain cognitive biases that affect good decision making, including loss aversion, where losses are more painful than gains are pleasurable, as well as the peak-end effect, where we judge our memories at their most intense rather than the total sum. Daniel shares that being aware of these biases, coupled with systematic data could lead to better decision making.
No coding, just a few clicks.
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