Zing Data, Mozart Data Partner to Put Hundreds of Data Sources in the Palm of Your Hand

Zing Data, a mobile-first platform for data analysis and collaboration, partners with Mozart Data, a full-service modern data platform for centralizing, organizing, and analyzing data.

This means that data from 300+ sources can be queried and visualized in a few taps from any Zing’s native iOS and Android apps, as well as the web. This partnership empowers even beginners to unify data from Stripe, Salesforce, Sendgrid, Workday, Facebook Ads, Google Ads, and other common data sources into analysis-ready datasets which can be used across a company – enabling nearly anybody at a company to query, visualize, and collaborate even when away from their desk.

“Nearly 80% of the global workforce is ‘deskless’ and the remaining 20% still has to go to the DMV, their kids’ soccer game, or wants to be productive on the go. Zing is dedicated to making it easy for them to use data from a phone.” said Zack Hendlin, CEO of Zing Data.

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Traditionally, pulling in data from many sources required building connectors, writing data engineering pipelines, and running SQL queries. This meant that using data was limited to costly centralized data teams, where getting a pipeline built or a dashboard built could take weeks. This limits the ability for people to make quick decisions using data, and results in worse decision-making, negatively impacting executive teams and employees in the field.

“By partnering with Zing, Mozart Data customers have whole new ways to access their data in the field or on the go – and make better decisions faster,” said Peter Fishman, CEO of Mozart Data.

Mozart Data can help customers achieve a 76% decrease in time-to-insight, while saving 30% compared to assembling the data infrastructure on their own. This makes data accessible to tools like Zing, resulting in some customers 10xing the number of employees using data on a daily basis.

“With this partnership, Zing and Mozart empower small and mid-sized companies to operate like they have a full data engineering team, purpose-built infrastructure, and a huge team of analysts,” said Hendlin.

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