San Francisco-based startup Atlan has announced the successful completion of a $105 million Series C funding round, aimed at tackling the growing "data chaos" faced by enterprises. This financing boosts Atlan's valuation to over $750 million, with major contributions from Singapore's sovereign wealth fund GIC and Meritech Capital, alongside existing investors Salesforce Ventures and PeakXV Partners. The company plans to utilize this capital to enhance its unified control plane product, which integrates diverse data infrastructures—from data platforms like Databricks to Customer Relationship Management (CRM) tools such as Salesforce 360.
Atlan is poised to expand its reach to meet the increasing demand for effective data organization, particularly in the era of artificial intelligence (AI). Co-founder Prukalpa Sankar emphasized, “CIOs and CDOs are increasingly questioned by boards regarding their AI roadmaps. The challenge isn't AI models, but the availability of AI-ready data enriched with business context, trust, and security. Atlan is building the control plane for the data and AI stack, integrating trust and context into the digital fabric.”
Understanding Atlan's Data Management Strategy
The concept of data chaos is prevalent across organizations of all sizes. Businesses are utilizing a multitude of tools and producing colossal volumes of structured and unstructured data. This data is often scattered across various platforms, including major solutions like Snowflake, while much remains unutilized in silos. A recent study predicts that by 2025, 80% of the world’s data will be stored by enterprises.
Launched in 2020, Atlan consolidates various data sources into a cohesive platform, offering users a comprehensive view of their data assets while facilitating collaboration. Sankar describes the platform as a "home for data teams," emphasizing its utility for managing data workflows.
The foundation of Atlan’s platform is its ‘Metadata Lakehouse,’ which features connectivity with essential data tools and systems for efficient metadata synchronization. This allows the collection of various metadata types, including technical data locations, user interactions, operational flow, and compliance information.
On top of this foundational layer is a trust layer that provides access management, data estate analytics, and classification. Personalized modules enhance data discovery, offer business metrics glossaries, and support no-code data lineage, enabling teams to effectively collaborate and resolve data issues.
Sankar elaborated on these capabilities, noting, “Data Engineers can visualize lineage charts to assess the downstream impact of changes, automatically alerting affected business users. Business teams can find trusted data and use curated data products tailored to their roles, while data governance personnel can establish policies connected to data assets for timely alerts on compliance violations.”
Rapid Growth in the Data Infrastructure Sector
Despite its relatively recent entry into the data infrastructure market, Atlan has established a strong presence. The demand for its services has surged, especially with the advent of generative AI. In the past two years, Atlan’s revenues have increased over sevenfold, attracting major clients such as Cisco, Autodesk, Unilever, and Nasdaq.
“Clients are turning to us to prepare their data for AI, while also seeking to democratize data access across teams and deliver data products to their customers. We are increasingly recognized not just as a catalog or discovery tool, but as a metadata control plane that enhances data utilization,” Sankar stated.
The Atlan platform reportedly reduces the time spent by data practitioners on data discovery and comprehension by up to 95%. Compared to competitors like Informatica, Collibra, and Alation, Atlan claims a significant edge, winning three-quarters of new deals and offering an automated, rules-based approach to metadata management, including the industry's premier AI copilot for metadata creation.
Moving forward, Atlan plans to leverage its recent funding to enhance product development, integrations, and operational expansion, all aimed at addressing the current market's need for organized data solutions.
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