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{"id":35681,"date":"2023-06-22T22:01:59","date_gmt":"2023-06-22T22:01:59","guid":{"rendered":"https:\/\/scienceandnerds.com\/2023\/06\/22\/acryl-data-raises-21m-to-grow-its-enterprise-data-catalog-platform\/"},"modified":"2023-06-22T22:02:00","modified_gmt":"2023-06-22T22:02:00","slug":"acryl-data-raises-21m-to-grow-its-enterprise-data-catalog-platform","status":"publish","type":"post","link":"https:\/\/scienceandnerds.com\/2023\/06\/22\/acryl-data-raises-21m-to-grow-its-enterprise-data-catalog-platform\/","title":{"rendered":"Acryl Data raises $21M to grow its enterprise data catalog platform"},"content":{"rendered":"

Source:https:\/\/techcrunch.com\/2023\/06\/22\/acryl-data-raises-21m-to-grow-its-enterprise-data-catalog-platform\/<\/a><\/br>
\nAcryl Data raises $21M to grow its enterprise data catalog platform<\/br>
\n2023-06-22 22:01:59<\/br><\/p>\n

\n

With the explosion of different kinds of data, companies are struggling to realize meaningful value from their stored data. Data teams are overworked \u2014 forced to cater to the needs of disparate departments within an organization while trying to maintain data policies consistently.<\/p>\n

That\u2019s the shared thesis of Shirshanka Das and Swaroop Jagadish, at least, the co-founders of Acryl Data<\/a>, a startup providing tools to help companies organize and ostensibly better manage their data. Acryl today announced that it raised $21 million in a Series A round led by 8VC with participation from Sherpalo Ventures and Guillermo Rauch, founder and CEO of Vercel, bringing its total raised to $30 million.<\/p>\n

Prior to launching Acryl Data, Das was a principal staff software engineer at LinkedIn and, before that, a member of the technical teams first at PayPal and then at Yahoo! (full disclosure: TechCrunch\u2019s owner). Jagadish came to Acryl by way of Airbnb as well as LinkedIn and Yahoo!<\/p>\n

\u201cAcryl Data is a community-driven metadata platform that delivers central controls across the decentralized data stack,\u201d Jagadish, the CEO, told TechCrunch in an email interview. \u201cWith a mission to bring clarity to data, Acryl offers a data catalog with solutions for data discovery, governance, lineage and observability.\u201d<\/p>\n

What exactly is a data catalog? Well, it\u2019s an inventory of data assets in an organization. Data catalogs consist of metadata in which definitions of database objects are stored, such as base tables, indexes, users and user groups.<\/p>\n

Data catalogs are a dime a dozen \u2014 see startups such as Castor<\/a>, Stemma<\/a>, Select Star<\/a> and Alation<\/a> offer them, to name a few. But Jagadish argues that Acryl\u2019s approach offers several key advantages over rivals.<\/p>\n

Chief among them, Acryl\u2019s platform \u2014 which is built on the open source framework DataHub \u2014 operates on \u201cevent-driven\u201d metadata. By only performing operations when triggered, Acryl can reduce the cost of data catalog maintenance while enabling a range of trigger-based workflows, Jagadish claims.<\/p>\n

\u201cThe explosion of data over the past decade has led companies to embrace a range of new technologies, but has created a fragmented data landscape as well,\u201d he added. \u201cSome problems got easier, like data orchestration, transformation, storage, movement and visualization \u2014 but other problems re-emerged as challenges, like data discovery, data quality and data management. Attempts to solve the problem \u2014 like traditional governance and observability tools \u2014 have been unnecessarily siloed, leading to further inefficiencies and inconsistent solutions \u2026 Acryl is designed to help teams move from simple data visibility to data insight, from insight to action and from action to automation.\u201d<\/p>\n

Beyond this, Acryl offers an \u201cobservability\u201d module designed for monitoring data quality in real time. The module, aptly dubbed Observe, monitors and attempts to spot data quality issues \u2014 in theory helping to prevent data breakages and drive faster resolutions where they do occur.<\/p>\n

Using Acryl, customers can also perform metadata tests, which surface areas for cost optimization, like expensive or underused data assets. The configurable monitors driving these tests let users define and continuously evaluate a set of conditions on the data assets in an organization.<\/p>\n

\u201cOur most common \u2018competitor\u2019 is the status quo of custom development, as data engineers establish manual processes and protocols on their own rather than implement a more automated solution,\u201d Jagadish said.<\/p>\n

Acryl has ambitious plans for the future, including AI features that\u2019ll \u201cintelligently curate\u201d metadata and suggest business glossary tags and terms to more thoroughly document data catalogs. In addition, the company aims to launch an AI-powered tool to generate summaries that describe the key characteristics of a given data catalog, like its reliability and usage.<\/p>\n

Acryl, which has a 25-person workforce, isn\u2019t disclosing too much about its customer base. But the startup did reveal that it counts Notion, Zendesk, Robinhood, OVO Energy, BetterUp and Riskified among its clients.<\/p>\n

Das added that DataHub, which he founded while at LinkedIn and which Acryl\u2019s staff maintains, is used by companies like Pinterest, Stripe, Optum, Expedia, Saxo Bank and Peloton. He\u2019s optimistic that the features Acryl\u2019s building on top of DataHub will convince at least a few of those to convert.<\/p>\n

\u201cThe fast rate of change in the data ecosystem presents a challenge for businesses and vendors alike,\u201d Jagadish said. \u201cAs issues inevitably arise, Acryl increases productivity for data teams. Business users have a central resource to ask and address questions, rather than ad hoc processes for each issue, while data professionals can use Acryl\u2019s lineage and impact analysis features to reduce time to resolution of data issues significantly.\u201d<\/p>\n<\/p><\/div>\n

<\/br><\/br><\/br><\/p>\n

Science, Tech, Technology<\/br>
\n<\/br>
\nSource:https:\/\/techcrunch.com\/2023\/06\/22\/acryl-data-raises-21m-to-grow-its-enterprise-data-catalog-platform\/<\/a><\/br><\/br><\/p>\n","protected":false},"excerpt":{"rendered":"

Source:https:\/\/techcrunch.com\/2023\/06\/22\/acryl-data-raises-21m-to-grow-its-enterprise-data-catalog-platform\/ Acryl Data raises $21M to grow its enterprise data catalog platform 2023-06-22 22:01:59 With the explosion of different kinds of data, companies are struggling to realize meaningful value from their stored data. Data teams are overworked \u2014 forced to cater to the needs of disparate departments within an organization while trying to maintain data […]<\/p>\n","protected":false},"author":1,"featured_media":35682,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"nf_dc_page":"","om_disable_all_campaigns":false,"pagelayer_contact_templates":[],"_pagelayer_content":"","_jetpack_memberships_contains_paid_content":false,"footnotes":""},"categories":[26,17,8],"tags":[],"class_list":["post-35681","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-science","category-tech","category-technology"],"yoast_head":"\nAcryl Data raises $21M to grow its enterprise data catalog platform - Science and Nerds<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/scienceandnerds.com\/2023\/06\/22\/acryl-data-raises-21m-to-grow-its-enterprise-data-catalog-platform\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Acryl Data raises $21M to grow its enterprise data catalog platform - Science and Nerds\" \/>\n<meta property=\"og:description\" content=\"Source:https:\/\/techcrunch.com\/2023\/06\/22\/acryl-data-raises-21m-to-grow-its-enterprise-data-catalog-platform\/ Acryl Data raises $21M to grow its enterprise data catalog platform 2023-06-22 22:01:59 With the explosion of different kinds of data, companies are struggling to realize meaningful value from their stored data. 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