How any size business can supersize results with data visualization

From midsize companies and government organizations to global banks and professional sports teams, all types of businesses are using data visualization to help make sense of their data and to comprehend information quickly. Keep reading to learn how six organizations of all types and sizes are using data visualization to improve customer relationships, fight fraud and more.

Spotlight

nDimensional

nDimensional’s product, nD, is a full stack application development Platform-as-a-Service (PaaS) that allows companies to rapidly design, develop, deploy and operate AI, big data and IoT applications. nD empowers data-rich industries to drive real-time actions that quantitatively improve business outcomes – proven at enterprise scale – to bring the power of predictive insights and optimization to all vertical markets and value chains.

OTHER WHITEPAPERS
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DataOS®: A Paradigm Shift in Data Management – Creating Scalable Analytics

whitePaper | October 10, 2022

Companies undergoing digital transformation must make data available to all stakeholders. However, outdated security and governance tools can prevent companies from freeing their data without opening themselves up to new risks.

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Business Benefits of Investing in Data Privacy Management Programs

whitePaper | January 20, 2023

Organizations increasingly recognize that accountability through the implementation of a data privacy management program (DPMP) is essential to operate effectively in the modern digital economy. For many years, the focus of organizations in implementing a DPMP has been mainly to achieve compliance with data protection requirements. Today, many organizations have undergone a shift in understanding and realize that a DPMP is as critical for risk management and compliance as it is for enabling data strategy, building customer trust, winning business, and attracting company investment.

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Why Open Architectures Matter in BI: A White Paper on Openness

whitePaper | September 1, 2022

Lock-in occurs when the cost or effort of moving away from a particular choice (platform, vendor) outweighs the benefit of doing so, even if that choice is good for the business overall. The pain of moving is simply too great to consider doing it.

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Targeted Attack Analytics

whitePaper | December 16, 2019

Symantec combines targeted attack analytics with research from our Attack Investigator Team (AIT) to find advanced attacks; our analytics evolve to match new attack patterns. Breach detection is one example of how our analytics help stop deliberate incursions.

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Evolving Role of Data Scientist in the Age of Personalization

whitePaper | March 12, 2020

This point of view is an exploration of the possibilities engendered by rethinking the role of data scientists in the wake of industrial revolution. It might be claimed that current trends in industrial revolution reflect a paradigm shift towards data centric processing with data science playing an increasingly critical role. This point of view also explicitly highlights the potential role of Data scientists as an emerging phenomenon, and then to show some of the benefits that this role can bring as we move towards industrial disruption

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SQL to NoSQL: Architecture Differences and Considerations for Migration

whitePaper | May 26, 2022

Since their invention in 1970 by Edgar Codd, relational databases have served as the default data store for almost every IT organization, large or small. Today, the most iconic and familiar relational databases include IBM DB2, Oracle Database, Microsoft SQL Server, PostgreSQL, and MySQL.

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Spotlight

nDimensional

nDimensional’s product, nD, is a full stack application development Platform-as-a-Service (PaaS) that allows companies to rapidly design, develop, deploy and operate AI, big data and IoT applications. nD empowers data-rich industries to drive real-time actions that quantitatively improve business outcomes – proven at enterprise scale – to bring the power of predictive insights and optimization to all vertical markets and value chains.

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