Applying Hybrid Operational/Analytic Processing (Hoap) in the Real World

MariaDB

The need to monetize data has become a strategic imperative for businesses undergoing digital transformation, whether it’s using data to improve customer engagement, identify compelling opportunities or deliver actionable insight.
However, as businesses look to expand revenue-generating, customer-facing applications beyond operational processing to include analytics, they find themselves outgrowing the their transactional database. They need full operational and full analytic capabilities.
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Spotlight

A data analytics product of HCube that ships with in-memory databases, and on which industry-specific analytics dashboards are built.

OTHER ON-DEMAND WEBINARS

Make Big Data Work in the Cloud

waterlinedata.com

Watch Matt Aslett from 451 Research and MakeBigDataWork.org in this 45 minute educational webinar on how to make big data work in the cloud.As companies shift their Big Data to the cloud and hybrid environments, the need for Big Data analytics and a corresponding long-term analytics strategy has become increasingly critical. Heres your opportunity to listen to experienced Big Data practitioners articulate their best practices in building successful, long term analytics architectures.
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Why IBM for Sales Performance Management?

FinTech

Improve sales performance and operational efficiencies with better management of incentive compensation plans and smarter administration of sales territories and quotas. Get faster insights with advanced analytics.
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Lynx: A FAIR-fuelled Reference Data Integration & Look up Service at Roche

Roche, as a leading biopharmaceutical company and member of the Pistoia Alliance, has a diverse and distributed ecosystem of platforms to manage reference data standards used at different parts of the organization. These diverse reference data standards include ontologies and vocabularies to capture specifics of the research environment and also to describe how clinical trial data are collected, tabulated, analyzed, and finally submitted to regulatory authorities. In the context of the EDIS program, Roche has bridged these parts to improve reverse translation from studies into research and also embraced FAIR to emphasize machine-actionability and data-driven processes.
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Building the Road Map for Real-Time Data and Analytics

As organizations strive to be more competitive, they often need real-time insights; no one wants to make decisions based on stale data. TDWI research indicates that real-time data collection is already in the mainstream. Some use cases include inventory management, fulfillment, supply chain, and logistics in which retailers must be able to assess product availability and consumer demand in real time. Forward-looking organizations also want to enrich real-time data with other data types to provide even better analytics.
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