I recently caught up with Adam Weinstein, Co-founder & CEO of Cursor to discuss how his company’s technology solution enables a single conversation by serving both business users and data practitioners on the same platform. By working together, teams are able to extract more value from their data. Cursor is a data search and analytics hub used by teams at Apple, Slack, Atlassian, and more. Prior to this, Adam was a leader on LinkedIn’s analytics team and the head of data and analytics at Bright (an AI-powered recruiting platform acquired by LinkedIn for $130M). He was the first business intelligence team member at ExactTarget, which was acquired by Salesforce for $2.5B and today is at the core of Salesforce Marketing Cloud.
insideBIGDATA: As an overview for our readers, what is Cursor and how does it help users get more value from their data?
Adam Weinstein: Cursor is a data collaboration platform that helps anyone across an organization, from analysts to C-suite executives, find, understand, and use their data to get answers to the questions they grapple with on a daily basis (e.g., “What was our revenue in Q4 2016?”). To do this, Cursor searches across a company’s databases, applications and existing BI platforms (e.g. Tableau, PowerBI, Looker, and more) to help pinpoint where the best answers live. The platform catalogs previously written code to help users find queries which they can leverage or build upon – enabling them to avoid duplicative work and get better answers, faster. By serving both business users and data practitioners on the same platform, Cursor enables one conversation. Working together, teams are able to extract more value from their data.
insideBIGDATA: How does Cursor fill a need in the marketplace and stand out from others in the industry?
Adam Weinstein: Many companies continue to struggle with the sheer volume of data and the fact that it is distributed across the organization, often in inaccessible silos (e.g., local workstations). Add in quality issues and a lack of proper documentation for a company’s data, and you have real challenges. While recent technology helps users find data more efficiently — such as leveraging machine learning to identify the right data source for specific analysis — this still only solves part of the problem.
Cursor was designed with all of the capabilities of leading data discovery and data cataloging tools, but we go beyond mere cataloging and enable teams to use that data to communicate with their teams to get to insights faster. Cursor not only lets organizations search intelligently across data sources, but also query code. After speaking with various leaders across the data industry, we learned that they wanted the ability to sort through previously written queries, quickly learn how they have been used, who used them, and who the original author was. Cursor was designed to do that and to enable users to instantly leverage that code, determine its quality and usability, and use it to build something new. We believe that sharing the knowledge makes it even more valuable so we built a chat function into the platform. Users can communicate directly in the platform to get feedback and answers to questions immediately.
insideBIGDATA: What types of companies are using Cursor and who within that company typically benefits the most from it?
Adam Weinstein: Cursor is now being used by more than 500 leading organizations worldwide, including teams at Apple, Atlassian, and LinkedIn. We have everyone from Silicon Valley to Main Street who are using Cursor to collaborate on their company’s data. We created Cursor to make it easy for anyone in any organization to access it and start getting more value from their data, even with just one user. More users, however, drive the expansion of the platform’s cataloging scope, meaning each additional user can bring connections to new applications, databases or BI platforms helping to expand the conversation quickly. Most importantly, we designed Cursor to serve both technical and business users – helping bring everyone together to increase transparency to get better insights, faster.
insideBIGDATA: You’ve recently launched Cursor Enterprise – how does this help users get more from their data?
Adam Weinstein: Cursor Enterprise meets the needs of the world’s largest data-driven organizations through a host of new features. Most notably, our new federated query capabilities help make it easy to quickly blend data from multiple data sources. In addition, our new Automated Recommendations leverage machine learning to put relevant and actionable data into the hands of users faster — saving them the time from seeking it out themselves.
insideBIGDATA: What is on the horizon for Cursor in 2019?
Adam Weinstein: We will continue to expand the functionality of Cursor Enterprise. While Cursor already has robust functionality to support development work in SQL, we are adding support for Python Notebooks which are increasingly being used by Data Scientists to analyze large datasets. Leveraging Cursor to build a catalog of Python code with rich metadata will help Data Scientists better collaborate with their teams by pulling them into the conversation. Additionally, we’re always adding new integrations, with ElasticSearch, BiqQuery, Microsoft Dynamics, and several others on the near-term roadmap.
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