Building Analytics Platform for Operationalising Machine Learning

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Speakers from Philips, Micro Focus & Tech Mahindra

About this talk

Data science is shaping modern businesses into data-driven organisations, with data at the epicenter of boosted profits, saved costs, and industry disruption. Handling and managing Big Data has emerged as a key modern competitive advantage. Hence, having and maintaining a proper analytics platform is crucial for the development and growth of an organisation. But managing and analyzing all that data comes at a cost. Advanced analytics and machine learning projects only show benefits when put into production operation. Modern Organisations are looking to build a platform that can facilitate operationalising advanced analytics, including machine learning, and build deeper predictive analytics into their products & services. Join us for a discussion where industry speakers from Philips, Micro Focus & Tech Mahindra will present the intricacies of establishing an analytics platform that can build a culture of advanced big data analytics that help successfully operationalise machine learning: •How to identify the right fit analytics platforms to support ML •How to systematically productize machine learning & deploy analytical insights •The skills and resources needed for successfully setting up an analytics platform •The maintainability and scalability challenges •Recommendations for data and analytics leaders

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The Vertica Unified Analytics Platform is built to handle the most demanding analytic use cases and is trusted by thousands of leading data-driven enterprises around the world, including Etsy, Bank of America, Uber, and more. Based on a massively scalable architecture with a broad set of analytical functions spanning event and time series, pattern matching, geospatial, and built-in machine learning capability, Vertica enables data analytics teams to easily apply these powerful functions to large and demanding analytical workloads. Vertica unites the major public clouds and on-premises data centers, as needed, and integrates data in cloud object storage and HDFS without forcing any data movement. Available as a SaaS option, or as a customer-managed system, Vertica helps teams combine growing data siloes for a more complete view of available data. Vertica features separation of compute and storage, so teams can spin up storage and compute resources as needed, then spin down afterwards to reduce costs.