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Komprise today introduced its solution for organizations trying to make sense of large-scale scattered datasets, including files and objects that are distributed across cloud and local storage, as well as across multiple public and private clouds or multiple tiers of storage.
Komprise Deep Analytics Actions, a new component of the Komprise Intelligent Data Management platform, is designed to find and index relevant data wherever it lives and consolidate it for further analysis. For example, researchers at a pharmaceutical company can query and extract the files related to a specific experiment generated by a set of researchers. The researchers can then import this virtual data set into a data lake or data warehouse for further analysis, according to Komprise.
Komprise cofounder, president, and COO Krishna Subramanian said in an interview that Pfizer is one of several pharmaceutical companies (including “80% of the people who build COVID vaccines”) that uses the Komprise platform, which helped define the requirements for Deep Analytics Actions. The technology can be applied upfront to determine where data should be stored or on-demand for a specific analytic application.
“For example, an autonomous carmaker might have different datacenters where they’re collecting all their data, petabytes and petabytes of it, and want to gather together just the data about how the vehicle behaves at red lights, which might be 3% of that,” Subramanian said. Komprise can now create a centralized index based on data wherever it is stored, classified by both metadata (an explicit tag or the file’s creation data, type, or owner) and extended metadata (like a project name encoded in the file name or the directory where a file is stored), she said.
The cost of data consolidation and analysis
In the absence of automation and precise targeting, the data consolidation step can be time-consuming and expensive because of the data egress fees cloud vendors charge when data is exported out of a cloud provider. This issue is so common that it sometimes prevents companies from pursuing potentially fruitful data analysis, according to Komprise. With Deep Analytics Actions, only the data required for a specific analytic chore is moved.
“We see a lot of use cases for deep analytics actions at the university,” says Matt Madill, senior storage administrator at Duquesne University, in a quote for the press release. “For instance, different research groups have unique requirements which users can support with tagging so that those data sets can not only be discovered easily, but they can apply the appropriate data management policies to them for long-term storage. We’ll be able to give users the power to have better control of their data and let us know what to archive and when.”
Founded in 2014, privately held Komprise has raised $50.7 million to date. Other components of its platform help with tasks such as data migration to the cloud. Subramanian discussed the broader issues of unstructured data analysis in a July interview with VentureBeat.
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