Acryl Data Gains Momentum with $21 Million Series A Funding
Acryl Data, a dynamic player in the data management industry, has recently announced a successful round of Series A funding, during which it secured an impressive $21 million. With this infusion, the total funding for the Mountain View, California-based company, co-founded by CEO Swaroop Jagadish and CTO Shirshanka Das, now stands at $30 million.
Acryl Data’s flagship product, Acryl Cloud, is an enterprise-grade data management platform, powered by the open-source DataHub Project. The company has an active role in leading the DataHub Project and its community, which boasts over 7,500 data practitioners.
The product has garnered industry attention and has been adopted by companies including Stripe, Pinterest, and Optum, as well as Notion, Zendesk, Riskified, and MYOB. These companies leverage Acryl Cloud to foster collaboration on cutting-edge data management capabilities, providing their businesses with a much-needed competitive edge.
The platform is designed as a community-driven solution to data management, providing centralized control across decentralized data stacks. In addition to its top-tier Data Catalog, Acryl Cloud offers solutions for data governance and observability, all managed through a service that extends the DataHub Project’s open-source capabilities.
Acryl Cloud’s features aim to reduce friction in the operational management of data, enabling businesses to establish a single source of truth for documentation, streamline the discovery of trusted assets with automated data lineage, and strengthen connections across technical and non-technical teams through an automated governance engine.
In addition to the funding news, Acryl Data has announced the launch of Acryl Observe, a fully-integrated observability module aimed at enhancing data quality management. This new module serves to increase trust in an organization’s most valuable data assets.
Acryl Observe aims to provide a unified platform for data observability, governance, and discovery, thereby bridging the gap between data producer and consumer teams. This innovative product is currently in private beta, with a general release slated for later in 2023.
Acryl Data’s solutions have been instrumental in helping companies understand and manage their data costs. In some instances, companies have reported a reduction in their monthly data warehousing expenses by as much as 25%.
Automated data asset classification and impact analysis have also allowed teams to safely retire redundant assets, thus lowering the cost of data storage and computation without incident.
The company addresses the challenges posed by the explosion of data in recent years. It aims to overcome the fragmentation of data landscapes, characterized by siloed datasets, disparate tools, and a lack of unified control.
Acryl Cloud has been designed to confront these issues head-on, by providing an open control plane for data and integrating governance and observability tools, which were previously unnecessarily separated.
Future versions of the platform, fueled by the recent funding, are expected to incorporate generative AI capabilities. These enhancements are anticipated to not only bring intuitive discovery experiences based on natural language capabilities but also further reduce the manual labor involved in data curation.
Acryl Data’s commitment to providing a suite of integrated capabilities, such as a modern data catalog, an automation-driven governance console, and an observability engine, makes it a promising investment.
The open control plane is tailored to reduce complexity and accelerate innovation, thus bringing data teams closer to the business and enabling even casual users to interact directly with data insights.
The company is backed by 8VC, LinkedIn, and Insight Partners, who share Acryl Data’s vision of a future where enterprises can consolidate control of their data stack within a single platform.
There is a growing belief that Acryl Data can be the control plane to usher in the future of data innovations like data contracts, distributed data mesh architectures, and the broad changes that machine learning and AI promise to deliver.
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