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The Dawn of Postmodern Analytics
January 9, 2019
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Steppingblocks is a digital career counseling platform that analyzes millions of professional paths to help students map the right choices for their career development.
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.
whitePaper | November 26, 2019
Modernized organizations are leveraging the transformative benefits of predictive analytics to propel their business forward. Predictive analytics arm you with knowledge and insights that can make the difference between profits and losses. They use modeling, machine learning, and artificial intelligence to analyze current data and make predictions about the future. Every industry can benefit from predictive analytics. Those who ignore the potential here are squandering a huge opportunity to grow or create better experiences. The recent dramatic progress in AI-based predictive analytics and machine learning provides organizations with the power to unlock tremendous value from previously hard to decipher data. Through the power of AI-enabled infrastructure, you can harness the predictive analytics/machine learning wave and gain business advantages that will not only keep you in the game, but at the leading edge. Automated server capabilities and the right server for the job will get you where you need to go. This eBook focuses in on how server automation, along with the right servers for the workload, empowers companies to make great strides in the world of machine learning and predictive analytics.
whitePaper | February 7, 2020
Multiple studies have proven that, while the business demand for databases grows, operational teams are constrained by traditional, reactive processes. Combined with budgetary pressures, this causes them to fall short in meeting the demand in a timely fashion. In addition, as companies adopt cloud paradigms, operational teams must manage across on-premises and cloud environments with the same resources. To be effective, companies need to shift from a reactive posture to one of standardization and proactive analysis and planning by leveraging intuitive tooling to automate manually intensive and non-value adding activities and to deliver real-time insights.
whitePaper | November 15, 2019
We are living in an era of digital disruption. Multiple industries are being disrupted, or fear being disrupted in the near future. Business models are evolving to cater to the dynamic markets and digital transformation that seems to be the answer to changing business models. Digital transformation is rapidly becoming a key priority in most industries, as organizations adapt to changing markets by leveraging technologies to build IT-centric business models. In general, organizations are using digital transformation to reach their goals of achieving greater agility, improving operational efficiency, improving customer experiences, and developing new revenue streams.
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
Operational Acceptance Testing (OAT) is the penultimate phase of Acceptance Testing in a Software Testing Life cycle and is the last defence line between a software development project and deployment of software on production. FFor decedes, Operational Acceptance has been undermined and misunderstood. Where User Acceptance has been written about and hailed as a final phase in testing before production. User Acceptance is but one side of the coin, Operational Acceptance is the other.
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