Bridging to the Cloud: The Right Database Makes The Difference
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Predictive analytics can help drive significant improvement to an organization's bottom line.This eBook from Ventana Research explores the many ways businesses can use predictive analytics to grow revenue, shrink costs and improve margins.
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Machine learning automates the development of analytic models that can learn and make predictions on data. It has been one of the fastest growing disciplines within the world of statistics and data science, but the barrier to entry has been high.
Data science platforms are engines for creating machine-learning solutions. This report evaluates 16 providers of data science platforms.
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Introducing Notebooks: A power tool for data scientists Fast, flexible and collaborative data exploration and analysis Data exploration and analysis is a repetitive, iterative process, but in order to meet business demands, data scientists do not always have the luxury of long development cycles. What if data scientists could answer bigger and tougher questions faster? What if they could more easily and rapidly experiment, test hypotheses and work more collaboratively on interactive analytics?
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IBM named a leader for data science platforms
Data science platforms are engines for creating machine-learning solutions. This report evaluates 16 providers of data science platforms.
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The synergy between predictive analytics and decision optimization is critical to good decision making. Predictive analytics offers insights into likely future scenarios, and decision optimization prescribes best-action recommendations for how to respond to those scenarios given your business goals, business dynamics, and potential tradeoffs or consequences.
Together, predictive analytics and decision optimization provide organizations with the ability to turn insight into action—and action into positive outcomes.
In this white paper, you’ll gain a better understanding of:
Read the paper today to discover how to bridge the gap between insight and action.
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New technologies and practices such as containers and DevOps methodologies have transformed today's enterprise application environments. With these advancements in hand, organizations can become more agile, able to respond quicker than ever to customer needs and competitive demands. And yet, this modern application development environment often leads to new pain points for the teams responsible for ensuring application performance. These pain points include alert fatigue, data overload and intelligence gaps due to the lack of data correlation. How can these modern teams move fast and still develop top-performing apps?
In this paper, we answer that question by examining the tool capabilities required to monitor in modern environments, including advanced analytics, extensive integrations, and both agent and agentless technologies. In addition, we look at emerging organizational models that support the performance goals of agile teams.
Although cloud computing represents perhaps the biggest change to IT in recent history, it’s not as simple as it sounds. Despite a seemingly constant call to “move to the cloud,” businesses must navigate a wide variety of service offerings and deployment models to determine what’s best for their requirements.
Download this whitepaper to see how multi-cloud discovery addresses this challenge by providing insight into your assets and their relationship across every environment.