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GoldenSource launches cloud data services for data lakes and warehouses

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GoldenSource, an independent provider of Enterprise Data Management (EDM) and Master Data Management (MDM) solutions, has launched cloud data services for financial markets firms to better manage data into and within data lakes and warehouses.

GoldenSource, an independent provider of Enterprise Data Management (EDM) and Master Data Management (MDM) solutions, has launched cloud data services for financial markets firms to better manage data into and within data lakes and warehouses.

Cloud data platforms and warehouses, such as Snowflake, are the next frontiers in enterprise data management, promising numerous benefits to aid analytics, processing, and reporting for both investment managers and capital markets firms. 

Despite the growing ease at which valuable data is available, including various cloud data marketplaces, a significant challenge remains in structuring the data in a way that brings immediate value to the personas consuming these data sets. Bringing in data sets is challenging and there is lots of overhead. Source data formats either need to be replicated within the data lake or mapped to a schema within the lake, which is a resource-heavy process. 

GoldenSource, with its decades of experience as a leading provider of data management services, is now providing this infrastructure as a service, including data pipelines and cloud-ready data schemas, to enable market participants to harvest data for their data lakes in a more efficient and beneficial way. Core to the GoldenSource offering is its cloud data model, which can be embedded in any cloud data warehouse or lake, providing immediate structure in what would otherwise be a disorganised data swamp.

Users can take data from traditional sources or via the cloud marketplaces, and use GoldenSource’s pre-configured vendor connections and toolkits to transform and use the data in their preferred warehouse, including Cloudera, Snowflake, Databricks and Google Cloud Platform. This significantly reduces the overhead needed to quickly onboard and manage these data sets.

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