John L. Rueter, VP of MarketingEnterprises are inundated with data contained in databases, emails, documents, spreadsheets and more. Their ability to elevate this data has become a key differencing factor, helping them to reach the top of business world. However, enterprises spend far too much time and resources in integrating and on boarding the data before they can realize any value out of it. Addressing these concerns is Boston-based Cambridge Semantics which have developed a Smart Data Lake that links and contextualizes the data— structured or unstructured—allowing enterprises to automate big data management in order to best search, discover, and analyze all data without placing any burden on IT.
Cambridge Semantics offers ANZO Smart Data Lake (ASDL), a graph-based data management, data discovery and analytics solution that helps discover hidden relationships in enterprise data, offering unprecedented accelerated insight. While traditional data lake structure relies on merely capturing the name of an entity—an account, a product, or a person— ASDL catalogs data using active metadata management graph models that describe data at a business level, capable of addressing all enterprise data sources. Using a graph based data catalog, Enterprises can then browse and discover data sets of interest in a secure and governed environment. The solution’s role-based security assures that only appropriate users can access, analyze or create new data sets. In addition, ASDL’s data and model governance assure trustworthy data and insights as an enterprise’s Smart Data Lake grows with the scale of its business.
ASDL ingests both structured and unstructured data through horizontally scaled, automated ETL (Extract, Transform, Load) procedures and empowers the users to work with very large datasets of rich data in an interactive timeframe. Also, the solution supports connectivity to both internal and external sources—including cloud or on-premise data lakes. This democratization of data endues the users to find answers across the entire breadth of data without the need of any curation or cleansing.
Using the ANZO Graph Query Engine (AGQE)—ASDL works with the combination of data by deploying semantic graph models to describe every data relationship in graph forms targeted at precise user problems. These contextual models can be stored, re-purposed or, combined for future scenarios.
ASDL’s data and model governance assure trustworthy data and insights as an enterprise’s Smart Data Lake grows with the scale of its business
AGQE is a massively parallel and in-memory graph analytics platform capable of supporting more than a trillion triples (facts and relationships) at lightning speed for interactive analysis. Hence, businesses experience faster turnaround and accelerated insight, all while maintaining better data governance and provenance. John L. Rueter, VP of Marketing, Cambridge Semantics likes to call it, “Having a conversation with data.”
In one instance, a large diversified pharmaceutical company was in a dire need to derive value from third-party data-sets and proactive assessments across varied source of data which was suffering from expanding data-volumes. ANZO enabled users search the knowledgebase, define analytics, answer ad-hoc Common Intelligence (CI) queries, and create interactive executive dashboards that showcase the most relevant information. The client was able to disseminate the most relevant and complete data opportunities to decision makers. Moreover, a considerable number of manual searches were replaced by automated data collection by syndicating ANZO into their platform.
With a constant effort to bring a paradigm shift within the big data scenario, Cambridge Semantics plans to enhance their cloud capabilitiesas cloud computing (ad-hoc) can be made up-and-running without any huge upright investment. “Cloud computing has provided us with unlimited means to make life much easier for the users of our systems from a data-usage standpoint,” lauds Rueter. The company plans to continue its investment in pushing the boundaries and up their ante in their contribution to field of human and data communication.